{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Output\Hardwiring Committment.APPENDIX B.04-21-2023.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}22 Apr 2023, 09:52:24
{txt}
{com}. 
. 
. 
. **** APPENDIX B STATISTICAL ANALYSES: ALTERNATIVE MECHANISM MODELS ***
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. 
. *** NOTE 1: IN THE APPENDIX, WE ARE ONLY GOING TO REPORT THE CORRESPONDING FIGURE 2 TYPE ESTIMATES BASED ON THE IQR MARGINAL EFFECT CHANGE IN THE HAZARD RATIO HORIZONTAL PLOTS WITH 95% CIs ***
. 
. 
. *** NOTE 2: TO SIMPLIFY BOTH THE ANALYSES AND PRESENTATION, WE WILL ONLY PRESENT THE RESULTS FROM THE TWO-WAY FIXED EFFECTS MODEL SPECIFICATIONS [MODELS 2 & 4] ***
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. 
. 
. *** NOTE 3: CONSISTENT WITH THE THEORY -- ONLY GRAPHING THE INTERACTION EFFECT BETWEEN ZLOYALMEDIAN AND COVARIATE OF INTEREST FOR CONSISTENCY PURPOSES ***
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. 
. ** RETRIEVE SINGLE EVENT RECORDS DATABASE [N = 860 APPOINTEE OBSERVATIONS: 831 UNCENSORED OBSERVATIONS; 29 CENSORED OBSERVATIONS] **
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. 
. use "C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Data\Krause and Byers.SRD.06-03-2022.dta", replace
{txt}
{com}. 
. 
. *
. *
. 
. 
. ** GENERATE CENSORING VARIABLE FOR HOLDOVER APPOINTEES SERVING BETWEEN/ACROSS ADMINISTRATIONS [=1]; UNCENSRED OBSERVATIONS [=0] ** 
. 
. gen singleadmin_service=1 if holdover==0
{txt}(29 missing values generated)

{com}. *
. replace singleadmin_service=0 if holdover==1
{txt}(29 real changes made)

{com}. *
. *
. tab singleadmin_service

{txt}singleadmin {c |}
   _service {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}         29        3.37        3.37
{txt}          1 {c |}{res}        831       96.63      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        860      100.00
{txt}
{com}. 
. 
. ** SET FOR SURVIVAL DATA WITH A SINGLE RECORD PER APPOINTEE OBSERVATION [N = 860: UNCENSORED N = 831; CENSORED N = 29] ** 
. stset okapptdur, failure(singleadmin_service)

     {txt}failure event:  {res}singleadmin_service != 0 & singleadmin_service < .
{txt}obs. time interval:  {res}(0, okapptdur]
{txt} exit on or before:  {res}failure

{txt}{hline 78}
{res}        860{txt}  total observations
{res}          0{txt}  exclusions
{hline 78}
{res}        860{txt}  observations remaining, representing
{res}        831{txt}  failures in single-record/single-failure data
{res}    850,034{txt}  total analysis time at risk and under observation
                                                at risk from t = {res}        0
                                     {txt}earliest observed entry t = {res}        0
                                          {txt}last observed exit t = {res}    4,074
{txt}
{com}. 
. *
. *
. *
. *
. 
. ** ESTIMATE COX SEMIPARAMETRIC AND WEIBULL PARAMETRIC MODELS PRESENTED IN MANUSCRIPT [TABLE 1: MODELS 1 - 4] ** 
. 
. ** NOTE COVARIATES THAT VARY TRHOUGH TIME ARE BASED ON THE STARTING DATE OF APPOINTED SERVICE [I.E., "OKSTART....""]
. 
. 
. 
. 
. *************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
. *** APPENDIX ANALYSES B: ALTERNATIVE MECHANISMS ****
. 
. 
. *** FIRST, BEGIN WITH MANUSCRIPT REPORTED MODELS 2 & 4 -- AND FIGURE 2 FOR THE GRAPHICAL PRESENTATION TO BE INCLUDED IN THE APPENDIX DOCUMENT
. 
. 
. 
. 
. **** MODEL 2: COX MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. stcox   c.zloyalmedian##i.soubinaryagency2nom  zpecompmedian  zmecompmedian   toplevel2   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43,  hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur

{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
Iteration 0:   log pseudolikelihood = {res}-4793.4442
{txt}Iteration 1:   log pseudolikelihood = {res}-4497.4067
{txt}Iteration 2:   log pseudolikelihood = {res}-4471.0956
{txt}Iteration 3:   log pseudolikelihood = {res}-4470.7443
{txt}Iteration 4:   log pseudolikelihood = {res}-4470.7439
{txt}Refining estimates:
Iteration 0:   log pseudolikelihood = {res}-4470.7439

{txt}Cox regression -- Breslow method for ties

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
                                                {txt}Wald chi2({res}40{txt})    =  {res}  93737.48
{txt}Log pseudolikelihood =   {res}-4470.7439             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 100:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 35}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 36}{c |}{col 48}    Robust
{col 1}                                _t{col 36}{c |} Haz. Ratio{col 48}   Std. Err.{col 60}      z{col 68}   P>|z|{col 76}     [95% Con{col 89}f. Interval]
{hline 35}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}zloyalmedian {c |}{col 36}{res}{space 2} 1.385689{col 48}{space 2} .1605757{col 59}{space 1}    2.81{col 68}{space 3}0.005{col 76}{space 4} 1.104148{col 89}{space 3} 1.739019
{txt}{space 13}1.soubinaryagency2nom {c |}{col 36}{res}{space 2} 1.152291{col 48}{space 2} .1989596{col 59}{space 1}    0.82{col 68}{space 3}0.412{col 76}{space 4} .8214672{col 89}{space 3} 1.616346
{txt}{space 34} {c |}
soubinaryagency2nom#c.zloyalmedian {c |}
{space 32}1  {c |}{col 36}{res}{space 2} .6214336{col 48}{space 2} .0871684{col 59}{space 1}   -3.39{col 68}{space 3}0.001{col 76}{space 4} .4720596{col 89}{space 3}  .818074
{txt}{space 34} {c |}
{space 21}zpecompmedian {c |}{col 36}{res}{space 2} 1.033714{col 48}{space 2} .0821645{col 59}{space 1}    0.42{col 68}{space 3}0.677{col 76}{space 4} .8845916{col 89}{space 3} 1.207975
{txt}{space 21}zmecompmedian {c |}{col 36}{res}{space 2} .9793862{col 48}{space 2} .0669574{col 59}{space 1}   -0.30{col 68}{space 3}0.761{col 76}{space 4} .8565646{col 89}{space 3} 1.119819
{txt}{space 25}toplevel2 {c |}{col 36}{res}{space 2} .5103239{col 48}{space 2} .0549484{col 59}{space 1}   -6.25{col 68}{space 3}0.000{col 76}{space 4} .4132321{col 89}{space 3} .6302282
{txt}{space 14}presagencyideolalign {c |}{col 36}{res}{space 2} .6508912{col 48}{space 2} .1725959{col 59}{space 1}   -1.62{col 68}{space 3}0.105{col 76}{space 4} .3870762{col 89}{space 3} 1.094512
{txt}{space 12}presagencyideolopposed {c |}{col 36}{res}{space 2} .6205378{col 48}{space 2} .1670667{col 59}{space 1}   -1.77{col 68}{space 3}0.076{col 76}{space 4} .3661004{col 89}{space 3} 1.051808
{txt}{space 19}subagencydesign {c |}{col 36}{res}{space 2} 1.768227{col 48}{space 2} .3203508{col 59}{space 1}    3.15{col 68}{space 3}0.002{col 76}{space 4} 1.239725{col 89}{space 3} 2.522033
{txt}{space 12}standaloneagencydesign {c |}{col 36}{res}{space 2} 2.061222{col 48}{space 2} .6000132{col 59}{space 1}    2.48{col 68}{space 3}0.013{col 76}{space 4} 1.165047{col 89}{space 3} 3.646751
{txt}{space 8}okstartsenpolarizationmean {c |}{col 36}{res}{space 2} 1.66e-11{col 48}{space 2} 1.76e-10{col 59}{space 1}   -2.34{col 68}{space 3}0.019{col 76}{space 4} 1.54e-20{col 89}{space 3} .0178679
{txt}{space 11}okstartfilipresdistance {c |}{col 36}{res}{space 2} 1155.527{col 48}{space 2} 2625.988{col 59}{space 1}    3.10{col 68}{space 3}0.002{col 76}{space 4} 13.43959{col 89}{space 3} 99351.49
{txt}{space 23}okcrossover {c |}{col 36}{res}{space 2} .1648507{col 48}{space 2} .0356675{col 59}{space 1}   -8.33{col 68}{space 3}0.000{col 76}{space 4} .1078755{col 89}{space 3} .2519177
{txt}{space 20}okstartpresapp {c |}{col 36}{res}{space 2} .9897732{col 48}{space 2} .0046195{col 59}{space 1}   -2.20{col 68}{space 3}0.028{col 76}{space 4} .9807605{col 89}{space 3} .9988688
{txt}{space 15}okstartunemployment {c |}{col 36}{res}{space 2} 1.139291{col 48}{space 2} .0988381{col 59}{space 1}    1.50{col 68}{space 3}0.133{col 76}{space 4} .9611459{col 89}{space 3} 1.350454
{txt}{space 34} {c |}
{space 23}okstartadyr {c |}
{space 32}2  {c |}{col 36}{res}{space 2} 1.620165{col 48}{space 2} .3677176{col 59}{space 1}    2.13{col 68}{space 3}0.034{col 76}{space 4} 1.038407{col 89}{space 3} 2.527845
{txt}{space 32}3  {c |}{col 36}{res}{space 2} 3.954025{col 48}{space 2} .8766031{col 59}{space 1}    6.20{col 68}{space 3}0.000{col 76}{space 4} 2.560524{col 89}{space 3} 6.105902
{txt}{space 32}4  {c |}{col 36}{res}{space 2} 3.535386{col 48}{space 2}  1.19626{col 59}{space 1}    3.73{col 68}{space 3}0.000{col 76}{space 4} 1.821452{col 89}{space 3} 6.862082
{txt}{space 32}5  {c |}{col 36}{res}{space 2} 1.638361{col 48}{space 2} .4030985{col 59}{space 1}    2.01{col 68}{space 3}0.045{col 76}{space 4} 1.011537{col 89}{space 3}  2.65361
{txt}{space 32}6  {c |}{col 36}{res}{space 2} 3.699317{col 48}{space 2} .9103052{col 59}{space 1}    5.32{col 68}{space 3}0.000{col 76}{space 4} 2.283826{col 89}{space 3} 5.992113
{txt}{space 32}7  {c |}{col 36}{res}{space 2}  5.65147{col 48}{space 2} 1.733666{col 59}{space 1}    5.65{col 68}{space 3}0.000{col 76}{space 4} 3.097731{col 89}{space 3} 10.31049
{txt}{space 32}8  {c |}{col 36}{res}{space 2} 9.027404{col 48}{space 2} 3.467645{col 59}{space 1}    5.73{col 68}{space 3}0.000{col 76}{space 4} 4.252025{col 89}{space 3} 19.16594
{txt}{space 34} {c |}
{space 26}sbagency {c |}
{space 32}2  {c |}{col 36}{res}{space 2} 3.268191{col 48}{space 2} .9402642{col 59}{space 1}    4.12{col 68}{space 3}0.000{col 76}{space 4} 1.859582{col 89}{space 3} 5.743804
{txt}{space 32}3  {c |}{col 36}{res}{space 2} 2.070785{col 48}{space 2} .5439464{col 59}{space 1}    2.77{col 68}{space 3}0.006{col 76}{space 4} 1.237498{col 89}{space 3} 3.465179
{txt}{space 32}4  {c |}{col 36}{res}{space 2} 1.353112{col 48}{space 2}  .322891{col 59}{space 1}    1.27{col 68}{space 3}0.205{col 76}{space 4} .8476432{col 89}{space 3} 2.160005
{txt}{space 32}5  {c |}{col 36}{res}{space 2} 1.157977{col 48}{space 2} .3230165{col 59}{space 1}    0.53{col 68}{space 3}0.599{col 76}{space 4} .6702827{col 89}{space 3} 2.000514
{txt}{space 32}6  {c |}{col 36}{res}{space 2} 2.909858{col 48}{space 2} .7065463{col 59}{space 1}    4.40{col 68}{space 3}0.000{col 76}{space 4} 1.807967{col 89}{space 3} 4.683313
{txt}{space 32}7  {c |}{col 36}{res}{space 2} 1.994085{col 48}{space 2} .5981195{col 59}{space 1}    2.30{col 68}{space 3}0.021{col 76}{space 4} 1.107716{col 89}{space 3} 3.589706
{txt}{space 32}8  {c |}{col 36}{res}{space 2} 2.711405{col 48}{space 2} .7702176{col 59}{space 1}    3.51{col 68}{space 3}0.000{col 76}{space 4} 1.553807{col 89}{space 3} 4.731422
{txt}{space 32}9  {c |}{col 36}{res}{space 2} 2.476116{col 48}{space 2} .6707849{col 59}{space 1}    3.35{col 68}{space 3}0.001{col 76}{space 4} 1.456059{col 89}{space 3} 4.210787
{txt}{space 31}11  {c |}{col 36}{res}{space 2} 4.394187{col 48}{space 2} 1.419151{col 59}{space 1}    4.58{col 68}{space 3}0.000{col 76}{space 4} 2.333316{col 89}{space 3} 8.275293
{txt}{space 31}12  {c |}{col 36}{res}{space 2} 1.853924{col 48}{space 2}  .336007{col 59}{space 1}    3.41{col 68}{space 3}0.001{col 76}{space 4} 1.299629{col 89}{space 3} 2.644628
{txt}{space 31}13  {c |}{col 36}{res}{space 2} 1.752547{col 48}{space 2} .4423016{col 59}{space 1}    2.22{col 68}{space 3}0.026{col 76}{space 4} 1.068677{col 89}{space 3} 2.874041
{txt}{space 31}14  {c |}{col 36}{res}{space 2} 2.860757{col 48}{space 2} .8250644{col 59}{space 1}    3.64{col 68}{space 3}0.000{col 76}{space 4} 1.625504{col 89}{space 3} 5.034706
{txt}{space 31}15  {c |}{col 36}{res}{space 2} 1.779291{col 48}{space 2} .4856656{col 59}{space 1}    2.11{col 68}{space 3}0.035{col 76}{space 4} 1.042096{col 89}{space 3}  3.03799
{txt}{space 31}16  {c |}{col 36}{res}{space 2} .8685938{col 48}{space 2} .1319371{col 59}{space 1}   -0.93{col 68}{space 3}0.354{col 76}{space 4} .6449431{col 89}{space 3} 1.169801
{txt}{space 31}17  {c |}{col 36}{res}{space 2} 1.631593{col 48}{space 2} .1207942{col 59}{space 1}    6.61{col 68}{space 3}0.000{col 76}{space 4} 1.411216{col 89}{space 3} 1.886384
{txt}{space 31}18  {c |}{col 36}{res}{space 2} 2.208613{col 48}{space 2} .6426988{col 59}{space 1}    2.72{col 68}{space 3}0.006{col 76}{space 4} 1.248599{col 89}{space 3} 3.906756
{txt}{space 31}19  {c |}{col 36}{res}{space 2} .8145991{col 48}{space 2}  .127576{col 59}{space 1}   -1.31{col 68}{space 3}0.190{col 76}{space 4} .5992881{col 89}{space 3} 1.107267
{txt}{space 31}20  {c |}{col 36}{res}{space 2} .2521271{col 48}{space 2} .0811474{col 59}{space 1}   -4.28{col 68}{space 3}0.000{col 76}{space 4} .1341711{col 89}{space 3} .4737834
{txt}{space 31}21  {c |}{col 36}{res}{space 2} .8452074{col 48}{space 2} .0715444{col 59}{space 1}   -1.99{col 68}{space 3}0.047{col 76}{space 4} .7159974{col 89}{space 3} .9977347
{txt}{space 31}22  {c |}{col 36}{res}{space 2} .4743225{col 48}{space 2} .1708597{col 59}{space 1}   -2.07{col 68}{space 3}0.038{col 76}{space 4}  .234129{col 89}{space 3} .9609311
{txt}{space 31}23  {c |}{col 36}{res}{space 2} 1.028681{col 48}{space 2} .2622634{col 59}{space 1}    0.11{col 68}{space 3}0.912{col 76}{space 4} .6241169{col 89}{space 3} 1.695491
{txt}{space 31}24  {c |}{col 36}{res}{space 2} .3016769{col 48}{space 2} .1438047{col 59}{space 1}   -2.51{col 68}{space 3}0.012{col 76}{space 4} .1185188{col 89}{space 3} .7678859
{txt}{space 31}25  {c |}{col 36}{res}{space 2} 1.429821{col 48}{space 2} .1932887{col 59}{space 1}    2.64{col 68}{space 3}0.008{col 76}{space 4} 1.097016{col 89}{space 3}  1.86359
{txt}{space 31}26  {c |}{col 36}{res}{space 2} .7985169{col 48}{space 2} .1130966{col 59}{space 1}   -1.59{col 68}{space 3}0.112{col 76}{space 4} .6049586{col 89}{space 3} 1.054005
{txt}{space 31}27  {c |}{col 36}{res}{space 2}        1{col 48}{txt}  (omitted)
{space 31}28  {c |}{col 36}{res}{space 2} 1.566368{col 48}{space 2} .1479302{col 59}{space 1}    4.75{col 68}{space 3}0.000{col 76}{space 4} 1.301682{col 89}{space 3} 1.884875
{txt}{space 31}29  {c |}{col 36}{res}{space 2}  3.94769{col 48}{space 2} 1.373691{col 59}{space 1}    3.95{col 68}{space 3}0.000{col 76}{space 4}  1.99594{col 89}{space 3} 7.807978
{txt}{space 31}30  {c |}{col 36}{res}{space 2} 1.607636{col 48}{space 2} .4787072{col 59}{space 1}    1.59{col 68}{space 3}0.111{col 76}{space 4}   .89686{col 89}{space 3} 2.881713
{txt}{space 31}50  {c |}{col 36}{res}{space 2} 2.150532{col 48}{space 2} .4436304{col 59}{space 1}    3.71{col 68}{space 3}0.000{col 76}{space 4} 1.435333{col 89}{space 3} 3.222101
{txt}{space 31}51  {c |}{col 36}{res}{space 2} 3.473497{col 48}{space 2} .9447425{col 59}{space 1}    4.58{col 68}{space 3}0.000{col 76}{space 4} 2.038224{col 89}{space 3} 5.919456
{txt}{space 31}52  {c |}{col 36}{res}{space 2} 1.565314{col 48}{space 2} .5211938{col 59}{space 1}    1.35{col 68}{space 3}0.178{col 76}{space 4} .8150452{col 89}{space 3} 3.006223
{txt}{space 31}53  {c |}{col 36}{res}{space 2} 1.513868{col 48}{space 2} .1622943{col 59}{space 1}    3.87{col 68}{space 3}0.000{col 76}{space 4} 1.226973{col 89}{space 3} 1.867846
{txt}{space 31}54  {c |}{col 36}{res}{space 2} 1.780839{col 48}{space 2} .3605465{col 59}{space 1}    2.85{col 68}{space 3}0.004{col 76}{space 4} 1.197544{col 89}{space 3} 2.648243
{txt}{space 31}55  {c |}{col 36}{res}{space 2} 1.279158{col 48}{space 2} .4553753{col 59}{space 1}    0.69{col 68}{space 3}0.489{col 76}{space 4} .6366486{col 89}{space 3} 2.570092
{txt}{space 31}56  {c |}{col 36}{res}{space 2}   1.0262{col 48}{space 2} .3879511{col 59}{space 1}    0.07{col 68}{space 3}0.945{col 76}{space 4} .4891462{col 89}{space 3} 2.152909
{txt}{space 31}57  {c |}{col 36}{res}{space 2}        1{col 48}{txt}  (omitted)
{space 31}58  {c |}{col 36}{res}{space 2} 1.418405{col 48}{space 2} .4602064{col 59}{space 1}    1.08{col 68}{space 3}0.281{col 76}{space 4} .7509737{col 89}{space 3} 2.679017
{txt}{space 31}59  {c |}{col 36}{res}{space 2} .3575611{col 48}{space 2} .1310554{col 59}{space 1}   -2.81{col 68}{space 3}0.005{col 76}{space 4} .1743262{col 89}{space 3} .7333945
{txt}{space 31}60  {c |}{col 36}{res}{space 2} 1.117945{col 48}{space 2} .1726301{col 59}{space 1}    0.72{col 68}{space 3}0.470{col 76}{space 4} .8259998{col 89}{space 3} 1.513076
{txt}{space 31}61  {c |}{col 36}{res}{space 2}        1{col 48}{txt}  (omitted)
{space 34} {c |}
{space 28}reagan {c |}{col 36}{res}{space 2} .0558675{col 48}{space 2} .0531481{col 59}{space 1}   -3.03{col 68}{space 3}0.002{col 76}{space 4} .0086575{col 89}{space 3} .3605182
{txt}{space 28}bush41 {c |}{col 36}{res}{space 2} .1506936{col 48}{space 2} .0925721{col 59}{space 1}   -3.08{col 68}{space 3}0.002{col 76}{space 4}  .045206{col 89}{space 3} .5023352
{txt}{space 27}clinton {c |}{col 36}{res}{space 2} .6407045{col 48}{space 2} .3377118{col 59}{space 1}   -0.84{col 68}{space 3}0.398{col 76}{space 4} .2280311{col 89}{space 3} 1.800203
{txt}{space 28}bush43 {c |}{col 36}{res}{space 2} .2117962{col 48}{space 2}  .155203{col 59}{space 1}   -2.12{col 68}{space 3}0.034{col 76}{space 4} .0503689{col 89}{space 3} .8905816
{txt}{hline 35}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-4793.444{col 39}-4470.744{col 50}    40{col 58} 9021.488{col 69} 9211.765
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.soubinaryagency2nom#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.soubinaryagency2nom#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .5222964{col 26}{space 2} .1000269{col 37}{space 1}   -3.39{col 46}{space 3}0.001{col 54}{space 4} .3588396{col 67}{space 3} .7602102
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model2zloyal = r(table)
{txt}
{com}. mat list model2zloyal
{res}
{txt}model2zloyal[9,1]
               (1)
     b {res}  .52229641
{txt}    se {res}  .10002687
{txt}     z {res} -3.3915086
{txt}pvalue {res}  .00069509
{txt}    ll {res}  .35883961
{txt}    ul {res}  .76021023
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          1
{reset}
{com}. 
. 
. 
. 
. 
. 
. 
. 
. **** MODEL 4: WEIBULL MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. streg   c.zloyalmedian##i.soubinaryagency2nom  zpecompmedian  zmecompmedian   toplevel2   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43, distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-604.21225}  
Iteration 2:{space 3}log pseudolikelihood = {res:-499.15183}  
Iteration 3:{space 3}log pseudolikelihood = {res:-497.85317}  
Iteration 4:{space 3}log pseudolikelihood = {res:-497.85043}  
Iteration 5:{space 3}log pseudolikelihood = {res:-497.85043}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-497.85043             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 100:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 35}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 36}{c |}{col 48}    Robust
{col 1}                                _t{col 36}{c |} Haz. Ratio{col 48}   Std. Err.{col 60}      z{col 68}   P>|z|{col 76}     [95% Con{col 89}f. Interval]
{hline 35}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}zloyalmedian {c |}{col 36}{res}{space 2} 1.375024{col 48}{space 2} .1587628{col 59}{space 1}    2.76{col 68}{space 3}0.006{col 76}{space 4} 1.096551{col 89}{space 3} 1.724215
{txt}{space 13}1.soubinaryagency2nom {c |}{col 36}{res}{space 2} 1.153634{col 48}{space 2}  .205655{col 59}{space 1}    0.80{col 68}{space 3}0.423{col 76}{space 4} .8134419{col 89}{space 3} 1.636098
{txt}{space 34} {c |}
soubinaryagency2nom#c.zloyalmedian {c |}
{space 32}1  {c |}{col 36}{res}{space 2} .6306902{col 48}{space 2} .0869891{col 59}{space 1}   -3.34{col 68}{space 3}0.001{col 76}{space 4} .4812963{col 89}{space 3} .8264557
{txt}{space 34} {c |}
{space 21}zpecompmedian {c |}{col 36}{res}{space 2} 1.041572{col 48}{space 2} .0817388{col 59}{space 1}    0.52{col 68}{space 3}0.604{col 76}{space 4} .8930797{col 89}{space 3} 1.214755
{txt}{space 21}zmecompmedian {c |}{col 36}{res}{space 2} .9846415{col 48}{space 2}  .065965{col 59}{space 1}   -0.23{col 68}{space 3}0.817{col 76}{space 4}  .863481{col 89}{space 3} 1.122803
{txt}{space 25}toplevel2 {c |}{col 36}{res}{space 2} .5394921{col 48}{space 2} .0567041{col 59}{space 1}   -5.87{col 68}{space 3}0.000{col 76}{space 4} .4390544{col 89}{space 3} .6629058
{txt}{space 14}presagencyideolalign {c |}{col 36}{res}{space 2} .7369114{col 48}{space 2} .1849133{col 59}{space 1}   -1.22{col 68}{space 3}0.224{col 76}{space 4} .4506331{col 89}{space 3} 1.205057
{txt}{space 12}presagencyideolopposed {c |}{col 36}{res}{space 2} .6935274{col 48}{space 2} .1764129{col 59}{space 1}   -1.44{col 68}{space 3}0.150{col 76}{space 4}  .421253{col 89}{space 3} 1.141785
{txt}{space 19}subagencydesign {c |}{col 36}{res}{space 2} 1.685222{col 48}{space 2} .2970439{col 59}{space 1}    2.96{col 68}{space 3}0.003{col 76}{space 4} 1.192946{col 89}{space 3} 2.380637
{txt}{space 12}standaloneagencydesign {c |}{col 36}{res}{space 2} 1.743278{col 48}{space 2} .4804177{col 59}{space 1}    2.02{col 68}{space 3}0.044{col 76}{space 4} 1.015757{col 89}{space 3} 2.991874
{txt}{space 8}okstartsenpolarizationmean {c |}{col 36}{res}{space 2} 7.77e-11{col 48}{space 2} 8.13e-10{col 59}{space 1}   -2.23{col 68}{space 3}0.026{col 76}{space 4} 9.78e-20{col 89}{space 3} .0617804
{txt}{space 11}okstartfilipresdistance {c |}{col 36}{res}{space 2} 893.7962{col 48}{space 2} 2000.161{col 59}{space 1}    3.04{col 68}{space 3}0.002{col 76}{space 4} 11.12747{col 89}{space 3} 71792.74
{txt}{space 23}okcrossover {c |}{col 36}{res}{space 2} .1747373{col 48}{space 2}  .037021{col 59}{space 1}   -8.23{col 68}{space 3}0.000{col 76}{space 4} .1153572{col 89}{space 3} .2646835
{txt}{space 20}okstartpresapp {c |}{col 36}{res}{space 2} .9902345{col 48}{space 2} .0045307{col 59}{space 1}   -2.14{col 68}{space 3}0.032{col 76}{space 4} .9813942{col 89}{space 3} .9991544
{txt}{space 15}okstartunemployment {c |}{col 36}{res}{space 2} 1.130022{col 48}{space 2} .0980922{col 59}{space 1}    1.41{col 68}{space 3}0.159{col 76}{space 4} .9532305{col 89}{space 3} 1.339603
{txt}{space 34} {c |}
{space 23}okstartadyr {c |}
{space 32}2  {c |}{col 36}{res}{space 2} 1.653304{col 48}{space 2} .3679208{col 59}{space 1}    2.26{col 68}{space 3}0.024{col 76}{space 4}  1.06888{col 89}{space 3} 2.557268
{txt}{space 32}3  {c |}{col 36}{res}{space 2} 4.383809{col 48}{space 2} .9244283{col 59}{space 1}    7.01{col 68}{space 3}0.000{col 76}{space 4} 2.899719{col 89}{space 3} 6.627463
{txt}{space 32}4  {c |}{col 36}{res}{space 2} 3.942686{col 48}{space 2} 1.239194{col 59}{space 1}    4.36{col 68}{space 3}0.000{col 76}{space 4} 2.129403{col 89}{space 3} 7.300061
{txt}{space 32}5  {c |}{col 36}{res}{space 2}  1.52843{col 48}{space 2}  .378723{col 59}{space 1}    1.71{col 68}{space 3}0.087{col 76}{space 4} .9404376{col 89}{space 3} 2.484054
{txt}{space 32}6  {c |}{col 36}{res}{space 2} 3.451085{col 48}{space 2} .8518352{col 59}{space 1}    5.02{col 68}{space 3}0.000{col 76}{space 4} 2.127417{col 89}{space 3} 5.598333
{txt}{space 32}7  {c |}{col 36}{res}{space 2} 6.295532{col 48}{space 2} 1.865565{col 59}{space 1}    6.21{col 68}{space 3}0.000{col 76}{space 4} 3.522043{col 89}{space 3} 11.25305
{txt}{space 32}8  {c |}{col 36}{res}{space 2} 10.02152{col 48}{space 2} 3.814879{col 59}{space 1}    6.05{col 68}{space 3}0.000{col 76}{space 4} 4.752342{col 89}{space 3} 21.13291
{txt}{space 34} {c |}
{space 26}sbagency {c |}
{space 32}2  {c |}{col 36}{res}{space 2} 2.832157{col 48}{space 2}  .761487{col 59}{space 1}    3.87{col 68}{space 3}0.000{col 76}{space 4} 1.672065{col 89}{space 3} 4.797128
{txt}{space 32}3  {c |}{col 36}{res}{space 2} 1.808613{col 48}{space 2} .4552409{col 59}{space 1}    2.35{col 68}{space 3}0.019{col 76}{space 4} 1.104313{col 89}{space 3} 2.962097
{txt}{space 32}4  {c |}{col 36}{res}{space 2} 1.234729{col 48}{space 2} .2752436{col 59}{space 1}    0.95{col 68}{space 3}0.344{col 76}{space 4} .7976698{col 89}{space 3} 1.911261
{txt}{space 32}5  {c |}{col 36}{res}{space 2} 1.041834{col 48}{space 2} .2765581{col 59}{space 1}    0.15{col 68}{space 3}0.877{col 76}{space 4} .6192193{col 89}{space 3} 1.752882
{txt}{space 32}6  {c |}{col 36}{res}{space 2} 2.509995{col 48}{space 2} .5911122{col 59}{space 1}    3.91{col 68}{space 3}0.000{col 76}{space 4}  1.58202{col 89}{space 3} 3.982297
{txt}{space 32}7  {c |}{col 36}{res}{space 2} 1.786664{col 48}{space 2} .5124548{col 59}{space 1}    2.02{col 68}{space 3}0.043{col 76}{space 4} 1.018356{col 89}{space 3} 3.134631
{txt}{space 32}8  {c |}{col 36}{res}{space 2} 2.373431{col 48}{space 2} .6278618{col 59}{space 1}    3.27{col 68}{space 3}0.001{col 76}{space 4} 1.413194{col 89}{space 3}  3.98613
{txt}{space 32}9  {c |}{col 36}{res}{space 2} 2.225332{col 48}{space 2} .5587987{col 59}{space 1}    3.19{col 68}{space 3}0.001{col 76}{space 4} 1.360352{col 89}{space 3}  3.64031
{txt}{space 31}11  {c |}{col 36}{res}{space 2} 3.703864{col 48}{space 2} 1.144586{col 59}{space 1}    4.24{col 68}{space 3}0.000{col 76}{space 4} 2.021215{col 89}{space 3} 6.787308
{txt}{space 31}12  {c |}{col 36}{res}{space 2} 1.709868{col 48}{space 2}  .290355{col 59}{space 1}    3.16{col 68}{space 3}0.002{col 76}{space 4} 1.225798{col 89}{space 3} 2.385099
{txt}{space 31}13  {c |}{col 36}{res}{space 2} 1.544219{col 48}{space 2} .3641007{col 59}{space 1}    1.84{col 68}{space 3}0.065{col 76}{space 4} .9727696{col 89}{space 3} 2.451364
{txt}{space 31}14  {c |}{col 36}{res}{space 2} 2.418647{col 48}{space 2} .6620859{col 59}{space 1}    3.23{col 68}{space 3}0.001{col 76}{space 4} 1.414368{col 89}{space 3} 4.136017
{txt}{space 31}15  {c |}{col 36}{res}{space 2} 1.618903{col 48}{space 2} .4115568{col 59}{space 1}    1.90{col 68}{space 3}0.058{col 76}{space 4} .9836234{col 89}{space 3} 2.664483
{txt}{space 31}16  {c |}{col 36}{res}{space 2} .8490932{col 48}{space 2} .1381262{col 59}{space 1}   -1.01{col 68}{space 3}0.315{col 76}{space 4} .6172857{col 89}{space 3} 1.167951
{txt}{space 31}17  {c |}{col 36}{res}{space 2} 1.615731{col 48}{space 2} .1250727{col 59}{space 1}    6.20{col 68}{space 3}0.000{col 76}{space 4} 1.388283{col 89}{space 3} 1.880442
{txt}{space 31}18  {c |}{col 36}{res}{space 2} 1.938672{col 48}{space 2} .5299753{col 59}{space 1}    2.42{col 68}{space 3}0.015{col 76}{space 4} 1.134517{col 89}{space 3} 3.312817
{txt}{space 31}19  {c |}{col 36}{res}{space 2} .8042553{col 48}{space 2} .1243205{col 59}{space 1}   -1.41{col 68}{space 3}0.159{col 76}{space 4} .5940412{col 89}{space 3} 1.088858
{txt}{space 31}20  {c |}{col 36}{res}{space 2} .3030017{col 48}{space 2} .0883753{col 59}{space 1}   -4.09{col 68}{space 3}0.000{col 76}{space 4} .1710718{col 89}{space 3} .5366754
{txt}{space 31}21  {c |}{col 36}{res}{space 2} .8814764{col 48}{space 2} .0799942{col 59}{space 1}   -1.39{col 68}{space 3}0.164{col 76}{space 4}  .737843{col 89}{space 3}  1.05307
{txt}{space 31}22  {c |}{col 36}{res}{space 2} .5227794{col 48}{space 2} .1752233{col 59}{space 1}   -1.94{col 68}{space 3}0.053{col 76}{space 4} .2710291{col 89}{space 3} 1.008373
{txt}{space 31}23  {c |}{col 36}{res}{space 2}  1.17553{col 48}{space 2} .2936578{col 59}{space 1}    0.65{col 68}{space 3}0.517{col 76}{space 4} .7204371{col 89}{space 3} 1.918101
{txt}{space 31}24  {c |}{col 36}{res}{space 2} .3410356{col 48}{space 2} .1339979{col 59}{space 1}   -2.74{col 68}{space 3}0.006{col 76}{space 4} .1578883{col 89}{space 3} .7366299
{txt}{space 31}25  {c |}{col 36}{res}{space 2} 1.502269{col 48}{space 2} .2167586{col 59}{space 1}    2.82{col 68}{space 3}0.005{col 76}{space 4} 1.132218{col 89}{space 3} 1.993267
{txt}{space 31}26  {c |}{col 36}{res}{space 2}   .80574{col 48}{space 2} .1241772{col 59}{space 1}   -1.40{col 68}{space 3}0.161{col 76}{space 4} .5956778{col 89}{space 3} 1.089879
{txt}{space 31}27  {c |}{col 36}{res}{space 2}        1{col 48}{txt}  (omitted)
{space 31}28  {c |}{col 36}{res}{space 2} 1.381344{col 48}{space 2} .1321202{col 59}{space 1}    3.38{col 68}{space 3}0.001{col 76}{space 4} 1.145217{col 89}{space 3} 1.666157
{txt}{space 31}29  {c |}{col 36}{res}{space 2} 3.335883{col 48}{space 2} 1.073496{col 59}{space 1}    3.74{col 68}{space 3}0.000{col 76}{space 4} 1.775383{col 89}{space 3} 6.268009
{txt}{space 31}30  {c |}{col 36}{res}{space 2} 1.401228{col 48}{space 2} .4054011{col 59}{space 1}    1.17{col 68}{space 3}0.244{col 76}{space 4} .7947687{col 89}{space 3} 2.470456
{txt}{space 31}50  {c |}{col 36}{res}{space 2} 1.941637{col 48}{space 2} .3765196{col 59}{space 1}    3.42{col 68}{space 3}0.001{col 76}{space 4} 1.327713{col 89}{space 3} 2.839435
{txt}{space 31}51  {c |}{col 36}{res}{space 2} 3.049867{col 48}{space 2}  .774135{col 59}{space 1}    4.39{col 68}{space 3}0.000{col 76}{space 4} 1.854487{col 89}{space 3} 5.015772
{txt}{space 31}52  {c |}{col 36}{res}{space 2} 1.571156{col 48}{space 2} .5056538{col 59}{space 1}    1.40{col 68}{space 3}0.160{col 76}{space 4} .8361271{col 89}{space 3} 2.952339
{txt}{space 31}53  {c |}{col 36}{res}{space 2} 1.501159{col 48}{space 2} .1594852{col 59}{space 1}    3.82{col 68}{space 3}0.000{col 76}{space 4} 1.218973{col 89}{space 3} 1.848671
{txt}{space 31}54  {c |}{col 36}{res}{space 2} 1.599048{col 48}{space 2} .3037601{col 59}{space 1}    2.47{col 68}{space 3}0.013{col 76}{space 4} 1.101957{col 89}{space 3} 2.320376
{txt}{space 31}55  {c |}{col 36}{res}{space 2} 1.062978{col 48}{space 2} .3619615{col 59}{space 1}    0.18{col 68}{space 3}0.858{col 76}{space 4}  .545351{col 89}{space 3} 2.071917
{txt}{space 31}56  {c |}{col 36}{res}{space 2} .9789283{col 48}{space 2}  .357858{col 59}{space 1}   -0.06{col 68}{space 3}0.954{col 76}{space 4} .4781728{col 89}{space 3} 2.004089
{txt}{space 31}57  {c |}{col 36}{res}{space 2}        1{col 48}{txt}  (omitted)
{space 31}58  {c |}{col 36}{res}{space 2} 1.157172{col 48}{space 2} .3752958{col 59}{space 1}    0.45{col 68}{space 3}0.653{col 76}{space 4} .6128225{col 89}{space 3} 2.185047
{txt}{space 31}59  {c |}{col 36}{res}{space 2} .3777419{col 48}{space 2} .0908125{col 59}{space 1}   -4.05{col 68}{space 3}0.000{col 76}{space 4} .2358081{col 89}{space 3} .6051062
{txt}{space 31}60  {c |}{col 36}{res}{space 2} .9463974{col 48}{space 2} .1372484{col 59}{space 1}   -0.38{col 68}{space 3}0.704{col 76}{space 4} .7122471{col 89}{space 3} 1.257524
{txt}{space 31}61  {c |}{col 36}{res}{space 2}        1{col 48}{txt}  (omitted)
{space 34} {c |}
{space 28}reagan {c |}{col 36}{res}{space 2} .0624967{col 48}{space 2} .0587982{col 59}{space 1}   -2.95{col 68}{space 3}0.003{col 76}{space 4} .0098862{col 89}{space 3} .3950805
{txt}{space 28}bush41 {c |}{col 36}{res}{space 2} .1549419{col 48}{space 2} .0945989{col 59}{space 1}   -3.05{col 68}{space 3}0.002{col 76}{space 4} .0468244{col 89}{space 3} .5127019
{txt}{space 27}clinton {c |}{col 36}{res}{space 2} .6171753{col 48}{space 2}  .330683{col 59}{space 1}   -0.90{col 68}{space 3}0.368{col 76}{space 4} .2159405{col 89}{space 3} 1.763936
{txt}{space 28}bush43 {c |}{col 36}{res}{space 2} .2147036{col 48}{space 2} .1571096{col 59}{space 1}   -2.10{col 68}{space 3}0.036{col 76}{space 4} .0511648{col 89}{space 3} .9009633
{txt}{space 29}_cons {c |}{col 36}{res}{space 2}  .000333{col 48}{space 2} .0018214{col 59}{space 1}   -1.46{col 68}{space 3}0.143{col 76}{space 4} 7.35e-09{col 89}{space 3} 15.09087
{txt}{hline 35}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 29}/ln_p {c |}{col 36}{res}{space 2} .9878179{col 48}{space 2} .0303399{col 59}{space 1}   32.56{col 68}{space 3}0.000{col 76}{space 4} .9283529{col 89}{space 3} 1.047283
{txt}{hline 35}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                                 p {c |}{col 36}{res}{space 2} 2.685368{col 48}{space 2} .0814737{col 76}{space 4} 2.530338{col 89}{space 3} 2.849897
{txt}                               1/p {c |}{col 36}{res}{space 2} .3723884{col 48}{space 2} .0112982{col 76}{space 4} .3508898{col 89}{space 3} .3952041
{txt}{hline 35}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-830.8551{col 39}-497.8504{col 50}    24{col 58} 1043.701{col 69} 1157.867
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.soubinaryagency2nom#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.soubinaryagency2nom#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .5329473{col 26}{space 2} .1003618{col 37}{space 1}   -3.34{col 46}{space 3}0.001{col 54}{space 4} .3684601{col 67}{space 3} .7708644
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix model4zloyal = r(table)
{txt}
{com}. mat list model4zloyal
{res}
{txt}model4zloyal[9,1]
               (1)
     b {res}  .53294727
{txt}    se {res}  .10036181
{txt}     z {res} -3.3419205
{txt}pvalue {res}  .00083201
{txt}    ll {res}   .3684601
{txt}    ul {res}  .77086444
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          1
{reset}
{com}. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. ** Generate 'manual' interaction variable ** 
. generate loyalppdiff = soubinaryagency2nom*zloyalmedian
{txt}
{com}. 
. ** Re-Estimate Model 4  with 'manual' interaction variable **
. streg   zloyalmedian soubinaryagency2nom loyalppdiff  zpecompmedian  zmecompmedian   toplevel2   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i.okstartadyr i.sbagency reagan bush41 clinton bush43, distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-604.21225}  
Iteration 2:{space 3}log pseudolikelihood = {res:-499.15183}  
Iteration 3:{space 3}log pseudolikelihood = {res:-497.85317}  
Iteration 4:{space 3}log pseudolikelihood = {res:-497.85043}  
Iteration 5:{space 3}log pseudolikelihood = {res:-497.85043}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-497.85043             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} 1.375024{col 40}{space 2} .1587628{col 51}{space 1}    2.76{col 60}{space 3}0.006{col 68}{space 4} 1.096551{col 81}{space 3} 1.724215
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.153634{col 40}{space 2}  .205655{col 51}{space 1}    0.80{col 60}{space 3}0.423{col 68}{space 4} .8134419{col 81}{space 3} 1.636098
{txt}{space 15}loyalppdiff {c |}{col 28}{res}{space 2} .6306902{col 40}{space 2} .0869891{col 51}{space 1}   -3.34{col 60}{space 3}0.001{col 68}{space 4} .4812963{col 81}{space 3} .8264557
{txt}{space 13}zpecompmedian {c |}{col 28}{res}{space 2} 1.041572{col 40}{space 2} .0817388{col 51}{space 1}    0.52{col 60}{space 3}0.604{col 68}{space 4} .8930797{col 81}{space 3} 1.214755
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9846415{col 40}{space 2}  .065965{col 51}{space 1}   -0.23{col 60}{space 3}0.817{col 68}{space 4}  .863481{col 81}{space 3} 1.122803
{txt}{space 17}toplevel2 {c |}{col 28}{res}{space 2} .5394921{col 40}{space 2} .0567041{col 51}{space 1}   -5.87{col 60}{space 3}0.000{col 68}{space 4} .4390544{col 81}{space 3} .6629058
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .7369114{col 40}{space 2} .1849133{col 51}{space 1}   -1.22{col 60}{space 3}0.224{col 68}{space 4} .4506331{col 81}{space 3} 1.205057
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .6935274{col 40}{space 2} .1764129{col 51}{space 1}   -1.44{col 60}{space 3}0.150{col 68}{space 4}  .421253{col 81}{space 3} 1.141785
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.685222{col 40}{space 2} .2970439{col 51}{space 1}    2.96{col 60}{space 3}0.003{col 68}{space 4} 1.192946{col 81}{space 3} 2.380637
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.743278{col 40}{space 2} .4804177{col 51}{space 1}    2.02{col 60}{space 3}0.044{col 68}{space 4} 1.015757{col 81}{space 3} 2.991874
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 7.77e-11{col 40}{space 2} 8.13e-10{col 51}{space 1}   -2.23{col 60}{space 3}0.026{col 68}{space 4} 9.78e-20{col 81}{space 3} .0617804
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 893.7962{col 40}{space 2} 2000.161{col 51}{space 1}    3.04{col 60}{space 3}0.002{col 68}{space 4} 11.12747{col 81}{space 3} 71792.74
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1747373{col 40}{space 2}  .037021{col 51}{space 1}   -8.23{col 60}{space 3}0.000{col 68}{space 4} .1153572{col 81}{space 3} .2646835
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9902345{col 40}{space 2} .0045307{col 51}{space 1}   -2.14{col 60}{space 3}0.032{col 68}{space 4} .9813942{col 81}{space 3} .9991544
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.130022{col 40}{space 2} .0980922{col 51}{space 1}    1.41{col 60}{space 3}0.159{col 68}{space 4} .9532305{col 81}{space 3} 1.339603
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.653304{col 40}{space 2} .3679208{col 51}{space 1}    2.26{col 60}{space 3}0.024{col 68}{space 4}  1.06888{col 81}{space 3} 2.557268
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.383809{col 40}{space 2} .9244283{col 51}{space 1}    7.01{col 60}{space 3}0.000{col 68}{space 4} 2.899719{col 81}{space 3} 6.627463
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 3.942686{col 40}{space 2} 1.239194{col 51}{space 1}    4.36{col 60}{space 3}0.000{col 68}{space 4} 2.129403{col 81}{space 3} 7.300061
{txt}{space 24}5  {c |}{col 28}{res}{space 2}  1.52843{col 40}{space 2}  .378723{col 51}{space 1}    1.71{col 60}{space 3}0.087{col 68}{space 4} .9404376{col 81}{space 3} 2.484054
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.451085{col 40}{space 2} .8518352{col 51}{space 1}    5.02{col 60}{space 3}0.000{col 68}{space 4} 2.127417{col 81}{space 3} 5.598333
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.295532{col 40}{space 2} 1.865565{col 51}{space 1}    6.21{col 60}{space 3}0.000{col 68}{space 4} 3.522043{col 81}{space 3} 11.25305
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 10.02152{col 40}{space 2} 3.814879{col 51}{space 1}    6.05{col 60}{space 3}0.000{col 68}{space 4} 4.752342{col 81}{space 3} 21.13291
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 2.832157{col 40}{space 2}  .761487{col 51}{space 1}    3.87{col 60}{space 3}0.000{col 68}{space 4} 1.672065{col 81}{space 3} 4.797128
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.808613{col 40}{space 2} .4552409{col 51}{space 1}    2.35{col 60}{space 3}0.019{col 68}{space 4} 1.104313{col 81}{space 3} 2.962097
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.234729{col 40}{space 2} .2752436{col 51}{space 1}    0.95{col 60}{space 3}0.344{col 68}{space 4} .7976698{col 81}{space 3} 1.911261
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.041834{col 40}{space 2} .2765581{col 51}{space 1}    0.15{col 60}{space 3}0.877{col 68}{space 4} .6192193{col 81}{space 3} 1.752882
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 2.509995{col 40}{space 2} .5911122{col 51}{space 1}    3.91{col 60}{space 3}0.000{col 68}{space 4}  1.58202{col 81}{space 3} 3.982297
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.786664{col 40}{space 2} .5124548{col 51}{space 1}    2.02{col 60}{space 3}0.043{col 68}{space 4} 1.018356{col 81}{space 3} 3.134631
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.373431{col 40}{space 2} .6278618{col 51}{space 1}    3.27{col 60}{space 3}0.001{col 68}{space 4} 1.413194{col 81}{space 3}  3.98613
{txt}{space 24}9  {c |}{col 28}{res}{space 2} 2.225332{col 40}{space 2} .5587987{col 51}{space 1}    3.19{col 60}{space 3}0.001{col 68}{space 4} 1.360352{col 81}{space 3}  3.64031
{txt}{space 23}11  {c |}{col 28}{res}{space 2} 3.703864{col 40}{space 2} 1.144586{col 51}{space 1}    4.24{col 60}{space 3}0.000{col 68}{space 4} 2.021215{col 81}{space 3} 6.787308
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 1.709868{col 40}{space 2}  .290355{col 51}{space 1}    3.16{col 60}{space 3}0.002{col 68}{space 4} 1.225798{col 81}{space 3} 2.385099
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.544219{col 40}{space 2} .3641007{col 51}{space 1}    1.84{col 60}{space 3}0.065{col 68}{space 4} .9727696{col 81}{space 3} 2.451364
{txt}{space 23}14  {c |}{col 28}{res}{space 2} 2.418647{col 40}{space 2} .6620859{col 51}{space 1}    3.23{col 60}{space 3}0.001{col 68}{space 4} 1.414368{col 81}{space 3} 4.136017
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.618903{col 40}{space 2} .4115568{col 51}{space 1}    1.90{col 60}{space 3}0.058{col 68}{space 4} .9836234{col 81}{space 3} 2.664483
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8490932{col 40}{space 2} .1381262{col 51}{space 1}   -1.01{col 60}{space 3}0.315{col 68}{space 4} .6172857{col 81}{space 3} 1.167951
{txt}{space 23}17  {c |}{col 28}{res}{space 2} 1.615731{col 40}{space 2} .1250727{col 51}{space 1}    6.20{col 60}{space 3}0.000{col 68}{space 4} 1.388283{col 81}{space 3} 1.880442
{txt}{space 23}18  {c |}{col 28}{res}{space 2} 1.938672{col 40}{space 2} .5299753{col 51}{space 1}    2.42{col 60}{space 3}0.015{col 68}{space 4} 1.134517{col 81}{space 3} 3.312817
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .8042553{col 40}{space 2} .1243205{col 51}{space 1}   -1.41{col 60}{space 3}0.159{col 68}{space 4} .5940412{col 81}{space 3} 1.088858
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .3030017{col 40}{space 2} .0883753{col 51}{space 1}   -4.09{col 60}{space 3}0.000{col 68}{space 4} .1710718{col 81}{space 3} .5366754
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .8814764{col 40}{space 2} .0799942{col 51}{space 1}   -1.39{col 60}{space 3}0.164{col 68}{space 4}  .737843{col 81}{space 3}  1.05307
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .5227794{col 40}{space 2} .1752233{col 51}{space 1}   -1.94{col 60}{space 3}0.053{col 68}{space 4} .2710291{col 81}{space 3} 1.008373
{txt}{space 23}23  {c |}{col 28}{res}{space 2}  1.17553{col 40}{space 2} .2936578{col 51}{space 1}    0.65{col 60}{space 3}0.517{col 68}{space 4} .7204371{col 81}{space 3} 1.918101
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .3410356{col 40}{space 2} .1339979{col 51}{space 1}   -2.74{col 60}{space 3}0.006{col 68}{space 4} .1578883{col 81}{space 3} .7366299
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.502269{col 40}{space 2} .2167586{col 51}{space 1}    2.82{col 60}{space 3}0.005{col 68}{space 4} 1.132218{col 81}{space 3} 1.993267
{txt}{space 23}26  {c |}{col 28}{res}{space 2}   .80574{col 40}{space 2} .1241772{col 51}{space 1}   -1.40{col 60}{space 3}0.161{col 68}{space 4} .5956778{col 81}{space 3} 1.089879
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.381344{col 40}{space 2} .1321202{col 51}{space 1}    3.38{col 60}{space 3}0.001{col 68}{space 4} 1.145217{col 81}{space 3} 1.666157
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 3.335883{col 40}{space 2} 1.073496{col 51}{space 1}    3.74{col 60}{space 3}0.000{col 68}{space 4} 1.775383{col 81}{space 3} 6.268009
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.401228{col 40}{space 2} .4054011{col 51}{space 1}    1.17{col 60}{space 3}0.244{col 68}{space 4} .7947687{col 81}{space 3} 2.470456
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 1.941637{col 40}{space 2} .3765196{col 51}{space 1}    3.42{col 60}{space 3}0.001{col 68}{space 4} 1.327713{col 81}{space 3} 2.839435
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 3.049867{col 40}{space 2}  .774135{col 51}{space 1}    4.39{col 60}{space 3}0.000{col 68}{space 4} 1.854487{col 81}{space 3} 5.015772
{txt}{space 23}52  {c |}{col 28}{res}{space 2} 1.571156{col 40}{space 2} .5056538{col 51}{space 1}    1.40{col 60}{space 3}0.160{col 68}{space 4} .8361271{col 81}{space 3} 2.952339
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.501159{col 40}{space 2} .1594852{col 51}{space 1}    3.82{col 60}{space 3}0.000{col 68}{space 4} 1.218973{col 81}{space 3} 1.848671
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.599048{col 40}{space 2} .3037601{col 51}{space 1}    2.47{col 60}{space 3}0.013{col 68}{space 4} 1.101957{col 81}{space 3} 2.320376
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.062978{col 40}{space 2} .3619615{col 51}{space 1}    0.18{col 60}{space 3}0.858{col 68}{space 4}  .545351{col 81}{space 3} 2.071917
{txt}{space 23}56  {c |}{col 28}{res}{space 2} .9789283{col 40}{space 2}  .357858{col 51}{space 1}   -0.06{col 60}{space 3}0.954{col 68}{space 4} .4781728{col 81}{space 3} 2.004089
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} 1.157172{col 40}{space 2} .3752958{col 51}{space 1}    0.45{col 60}{space 3}0.653{col 68}{space 4} .6128225{col 81}{space 3} 2.185047
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3777419{col 40}{space 2} .0908125{col 51}{space 1}   -4.05{col 60}{space 3}0.000{col 68}{space 4} .2358081{col 81}{space 3} .6051062
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .9463974{col 40}{space 2} .1372484{col 51}{space 1}   -0.38{col 60}{space 3}0.704{col 68}{space 4} .7122471{col 81}{space 3} 1.257524
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0624967{col 40}{space 2} .0587982{col 51}{space 1}   -2.95{col 60}{space 3}0.003{col 68}{space 4} .0098862{col 81}{space 3} .3950805
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1549419{col 40}{space 2} .0945989{col 51}{space 1}   -3.05{col 60}{space 3}0.002{col 68}{space 4} .0468244{col 81}{space 3} .5127019
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6171753{col 40}{space 2}  .330683{col 51}{space 1}   -0.90{col 60}{space 3}0.368{col 68}{space 4} .2159405{col 81}{space 3} 1.763936
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2147036{col 40}{space 2} .1571096{col 51}{space 1}   -2.10{col 60}{space 3}0.036{col 68}{space 4} .0511648{col 81}{space 3} .9009633
{txt}{space 21}_cons {c |}{col 28}{res}{space 2}  .000333{col 40}{space 2} .0018214{col 51}{space 1}   -1.46{col 60}{space 3}0.143{col 68}{space 4} 7.35e-09{col 81}{space 3} 15.09087
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9878179{col 40}{space 2} .0303399{col 51}{space 1}   32.56{col 60}{space 3}0.000{col 68}{space 4} .9283529{col 81}{space 3} 1.047283
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.685368{col 40}{space 2} .0814737{col 68}{space 4} 2.530338{col 81}{space 3} 2.849897
{txt}                       1/p {c |}{col 28}{res}{space 2} .3723884{col 40}{space 2} .0112982{col 68}{space 4} .3508898{col 81}{space 3} .3952041
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimates store model4b
{txt}
{com}. 
. margins, predict(median time) at(loyalppdiff=(-0.3960373 0.9692858))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 924.6994{col 26}{space 2} 26.60939{col 37}{space 1}   34.75{col 46}{space 3}0.000{col 54}{space 4} 872.5459{col 67}{space 3} 976.8528
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 1168.908{col 26}{space 2} 58.94499{col 37}{space 1}   19.83{col 46}{space 3}0.000{col 54}{space 4} 1053.378{col 67}{space 3} 1284.438
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(loyalppdiff=(-0.3960373 0.9692858))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}    10.06{col 38}{space 2}   0.0015
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2} 244.2082{col 26}{space 2} 77.00348{col 37}{space 5} 93.28416{col 51}{space 3} 395.1323
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix model4azloyal = r(table)
{txt}
{com}. mat list model4azloyal
{res}
{txt}model4azloyal[9,1]
            r2vs1.
              _at
     b {res} 244.20821
{txt}    se {res} 77.003481
{txt}     z {res} 3.1713918
{txt}pvalue {res}  .0015171
{txt}    ll {res} 93.284156
{txt}    ul {res} 395.13225
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         0
{reset}
{com}. 
. 
. 
. estimates restore model4b
{txt}(results {stata estimates replay model4b:model4b} are active now)

{com}. 
. margins, predict(median time) at(loyalppdiff=(-0.6451644 1.711348))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 885.9905{col 26}{space 2} 35.34227{col 37}{space 1}   25.07{col 46}{space 3}0.000{col 54}{space 4}  816.721{col 67}{space 3} 955.2601
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 1327.694{col 26}{space 2} 116.1924{col 37}{space 1}   11.43{col 46}{space 3}0.000{col 54}{space 4} 1099.961{col 67}{space 3} 1555.427
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, predict(median time) at(loyalppdiff=(-0.6451644 1.711348))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:loyalppdiff}{space 5}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     9.14{col 38}{space 2}   0.0025
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2} 441.7037{col 26}{space 2} 146.1002{col 37}{space 5} 155.3525{col 51}{space 3} 728.0549
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix model4bzloyal = r(table)
{txt}
{com}. mat list model4bzloyal
{res}
{txt}model4bzloyal[9,1]
            r2vs1.
              _at
     b {res}  441.7037
{txt}    se {res} 146.10022
{txt}     z {res} 3.0232925
{txt}pvalue {res}  .0025004
{txt}    ll {res} 155.35253
{txt}    ul {res} 728.05486
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         0
{reset}
{com}. 
. 
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. 
. 
. 
. 
. **** ALTERNATIVE MECHANISM B1: DOES POLICY PRIORITY DISTINCTION HAVE A DIFFERENTIAL EFFECT OF APPOINTEE MANAGERIAL COMPETENCE ON APPOINTEE TENURE? ***
. 
. 
. 
. 
. **** MODEL B1.1:  APPOINTEE MANAGERIAL COMPETENCE X POLICY PRIORITY AGENCY -- COX MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. stcox   zloyalmedian zpecompmedian  c.zmecompmedian##i.soubinaryagency2nom  toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign  standaloneagencydesign okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur

{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
Iteration 0:   log pseudolikelihood = {res}-4793.4442
{txt}Iteration 1:   log pseudolikelihood = {res}-4509.5937
{txt}Iteration 2:   log pseudolikelihood = {res}-4482.9756
{txt}Iteration 3:   log pseudolikelihood = {res} -4482.609
{txt}Iteration 4:   log pseudolikelihood = {res}-4482.6086
{txt}Refining estimates:
Iteration 0:   log pseudolikelihood = {res}-4482.6086

{txt}Cox regression -- Breslow method for ties

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
                                                {txt}Wald chi2({res}40{txt})    =  {res} 131364.15
{txt}Log pseudolikelihood =   {res}-4482.6086             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 101:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 36}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 37}{c |}{col 49}    Robust
{col 1}                                 _t{col 37}{c |} Haz. Ratio{col 49}   Std. Err.{col 61}      z{col 69}   P>|z|{col 77}     [95% Con{col 90}f. Interval]
{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}zloyalmedian {c |}{col 37}{res}{space 2} .9950902{col 49}{space 2} .0753237{col 60}{space 1}   -0.07{col 69}{space 3}0.948{col 77}{space 4} .8578877{col 90}{space 3} 1.154236
{txt}{space 22}zpecompmedian {c |}{col 37}{res}{space 2} 1.035425{col 49}{space 2} .0819681{col 60}{space 1}    0.44{col 69}{space 3}0.660{col 77}{space 4} .8866135{col 90}{space 3} 1.209213
{txt}{space 22}zmecompmedian {c |}{col 37}{res}{space 2} .9720201{col 49}{space 2} .0871509{col 60}{space 1}   -0.32{col 69}{space 3}0.752{col 77}{space 4}  .815374{col 90}{space 3}  1.15876
{txt}{space 14}1.soubinaryagency2nom {c |}{col 37}{res}{space 2} 1.047941{col 49}{space 2} .1751552{col 60}{space 1}    0.28{col 69}{space 3}0.779{col 77}{space 4} .7552054{col 90}{space 3} 1.454148
{txt}{space 35} {c |}
soubinaryagency2nom#c.zmecompmedian {c |}
{space 33}1  {c |}{col 37}{res}{space 2} 1.005933{col 49}{space 2} .0806056{col 60}{space 1}    0.07{col 69}{space 3}0.941{col 77}{space 4} .8597299{col 90}{space 3} 1.176998
{txt}{space 35} {c |}
{space 26}toplevel2 {c |}{col 37}{res}{space 2} .4999249{col 49}{space 2} .0541681{col 60}{space 1}   -6.40{col 69}{space 3}0.000{col 77}{space 4} .4042732{col 90}{space 3} .6182079
{txt}{space 15}presagencyideolalign {c |}{col 37}{res}{space 2} .6383764{col 49}{space 2} .1558335{col 60}{space 1}   -1.84{col 69}{space 3}0.066{col 77}{space 4} .3956315{col 90}{space 3} 1.030061
{txt}{space 13}presagencyideolopposed {c |}{col 37}{res}{space 2} .6189924{col 49}{space 2} .1563341{col 60}{space 1}   -1.90{col 69}{space 3}0.058{col 77}{space 4} .3773149{col 90}{space 3} 1.015469
{txt}{space 20}subagencydesign {c |}{col 37}{res}{space 2} 1.472653{col 49}{space 2} .2357614{col 60}{space 1}    2.42{col 69}{space 3}0.016{col 77}{space 4} 1.076041{col 90}{space 3} 2.015449
{txt}{space 13}standaloneagencydesign {c |}{col 37}{res}{space 2} 1.913833{col 49}{space 2} .4852199{col 60}{space 1}    2.56{col 69}{space 3}0.010{col 77}{space 4} 1.164384{col 90}{space 3}  3.14566
{txt}{space 9}okstartsenpolarizationmean {c |}{col 37}{res}{space 2} 5.74e-11{col 49}{space 2} 6.05e-10{col 60}{space 1}   -2.24{col 69}{space 3}0.025{col 77}{space 4} 6.15e-20{col 90}{space 3} .0535765
{txt}{space 12}okstartfilipresdistance {c |}{col 37}{res}{space 2} 604.0623{col 49}{space 2} 1418.902{col 60}{space 1}    2.73{col 69}{space 3}0.006{col 77}{space 4} 6.048756{col 90}{space 3} 60325.01
{txt}{space 24}okcrossover {c |}{col 37}{res}{space 2}  .169806{col 49}{space 2} .0384164{col 60}{space 1}   -7.84{col 69}{space 3}0.000{col 77}{space 4} .1089883{col 90}{space 3} .2645612
{txt}{space 21}okstartpresapp {c |}{col 37}{res}{space 2} .9919749{col 49}{space 2} .0046459{col 60}{space 1}   -1.72{col 69}{space 3}0.085{col 77}{space 4} .9829107{col 90}{space 3} 1.001123
{txt}{space 16}okstartunemployment {c |}{col 37}{res}{space 2} 1.130961{col 49}{space 2} .1068142{col 60}{space 1}    1.30{col 69}{space 3}0.193{col 77}{space 4} .9398429{col 90}{space 3} 1.360942
{txt}{space 35} {c |}
{space 24}okstartadyr {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 1.649601{col 49}{space 2} .3718629{col 60}{space 1}    2.22{col 69}{space 3}0.026{col 77}{space 4} 1.060464{col 90}{space 3} 2.566031
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 3.913285{col 49}{space 2} .9038363{col 60}{space 1}    5.91{col 69}{space 3}0.000{col 77}{space 4} 2.488529{col 90}{space 3} 6.153755
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 3.687598{col 49}{space 2} 1.207549{col 60}{space 1}    3.99{col 69}{space 3}0.000{col 77}{space 4} 1.940918{col 90}{space 3} 7.006157
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.638985{col 49}{space 2} .4083573{col 60}{space 1}    1.98{col 69}{space 3}0.047{col 77}{space 4} 1.005764{col 90}{space 3} 2.670878
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 3.762475{col 49}{space 2} .9598105{col 60}{space 1}    5.19{col 69}{space 3}0.000{col 77}{space 4} 2.282083{col 90}{space 3} 6.203201
{txt}{space 33}7  {c |}{col 37}{res}{space 2}   5.7425{col 49}{space 2} 1.773293{col 60}{space 1}    5.66{col 69}{space 3}0.000{col 77}{space 4}  3.13508{col 90}{space 3} 10.51849
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 8.953099{col 49}{space 2} 3.552075{col 60}{space 1}    5.52{col 69}{space 3}0.000{col 77}{space 4} 4.114012{col 90}{space 3} 19.48414
{txt}{space 35} {c |}
{space 27}sbagency {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 2.885277{col 49}{space 2} .7445907{col 60}{space 1}    4.11{col 69}{space 3}0.000{col 77}{space 4} 1.739889{col 90}{space 3} 4.784685
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 2.007248{col 49}{space 2} .4558127{col 60}{space 1}    3.07{col 69}{space 3}0.002{col 77}{space 4} 1.286196{col 90}{space 3} 3.132526
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 1.537485{col 49}{space 2} .3272654{col 60}{space 1}    2.02{col 69}{space 3}0.043{col 77}{space 4} 1.013039{col 90}{space 3} 2.333435
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.281385{col 49}{space 2} .3228239{col 60}{space 1}    0.98{col 69}{space 3}0.325{col 77}{space 4} .7820476{col 90}{space 3} 2.099548
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 3.011069{col 49}{space 2} .6573086{col 60}{space 1}    5.05{col 69}{space 3}0.000{col 77}{space 4} 1.962934{col 90}{space 3} 4.618871
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 1.975547{col 49}{space 2} .5211508{col 60}{space 1}    2.58{col 69}{space 3}0.010{col 77}{space 4} 1.177985{col 90}{space 3} 3.313104
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 2.523486{col 49}{space 2} .6243043{col 60}{space 1}    3.74{col 69}{space 3}0.000{col 77}{space 4} 1.553874{col 90}{space 3} 4.098133
{txt}{space 33}9  {c |}{col 37}{res}{space 2} 2.138152{col 49}{space 2} .5075688{col 60}{space 1}    3.20{col 69}{space 3}0.001{col 77}{space 4} 1.342686{col 90}{space 3} 3.404885
{txt}{space 32}11  {c |}{col 37}{res}{space 2} 3.818933{col 49}{space 2} 1.170634{col 60}{space 1}    4.37{col 69}{space 3}0.000{col 77}{space 4} 2.094207{col 90}{space 3} 6.964093
{txt}{space 32}12  {c |}{col 37}{res}{space 2} 2.084055{col 49}{space 2}  .384569{col 60}{space 1}    3.98{col 69}{space 3}0.000{col 77}{space 4} 1.451569{col 90}{space 3} 2.992132
{txt}{space 32}13  {c |}{col 37}{res}{space 2} 1.673762{col 49}{space 2} .3683064{col 60}{space 1}    2.34{col 69}{space 3}0.019{col 77}{space 4}   1.0874{col 90}{space 3}  2.57631
{txt}{space 32}14  {c |}{col 37}{res}{space 2} 2.621886{col 49}{space 2} .6535809{col 60}{space 1}    3.87{col 69}{space 3}0.000{col 77}{space 4} 1.608523{col 90}{space 3} 4.273664
{txt}{space 32}15  {c |}{col 37}{res}{space 2} 1.612119{col 49}{space 2} .3893519{col 60}{space 1}    1.98{col 69}{space 3}0.048{col 77}{space 4} 1.004196{col 90}{space 3} 2.588067
{txt}{space 32}16  {c |}{col 37}{res}{space 2} .8503665{col 49}{space 2} .1293751{col 60}{space 1}   -1.07{col 69}{space 3}0.287{col 77}{space 4} .6311085{col 90}{space 3} 1.145799
{txt}{space 32}17  {c |}{col 37}{res}{space 2} 1.614114{col 49}{space 2} .1334188{col 60}{space 1}    5.79{col 69}{space 3}0.000{col 77}{space 4} 1.372701{col 90}{space 3} 1.897984
{txt}{space 32}18  {c |}{col 37}{res}{space 2} 2.125472{col 49}{space 2} .5550579{col 60}{space 1}    2.89{col 69}{space 3}0.004{col 77}{space 4} 1.273995{col 90}{space 3} 3.546035
{txt}{space 32}19  {c |}{col 37}{res}{space 2} .7219654{col 49}{space 2} .1103216{col 60}{space 1}   -2.13{col 69}{space 3}0.033{col 77}{space 4} .5351143{col 90}{space 3} .9740613
{txt}{space 32}20  {c |}{col 37}{res}{space 2} .2779542{col 49}{space 2} .0852072{col 60}{space 1}   -4.18{col 69}{space 3}0.000{col 77}{space 4}  .152418{col 90}{space 3} .5068859
{txt}{space 32}21  {c |}{col 37}{res}{space 2} .9085506{col 49}{space 2} .0835611{col 60}{space 1}   -1.04{col 69}{space 3}0.297{col 77}{space 4} .7586868{col 90}{space 3} 1.088017
{txt}{space 32}22  {c |}{col 37}{res}{space 2} .5253498{col 49}{space 2} .1840829{col 60}{space 1}   -1.84{col 69}{space 3}0.066{col 77}{space 4} .2643547{col 90}{space 3} 1.044023
{txt}{space 32}23  {c |}{col 37}{res}{space 2} 1.107711{col 49}{space 2} .2553715{col 60}{space 1}    0.44{col 69}{space 3}0.657{col 77}{space 4} .7050022{col 90}{space 3} 1.740453
{txt}{space 32}24  {c |}{col 37}{res}{space 2} .2228479{col 49}{space 2} .1095014{col 60}{space 1}   -3.06{col 69}{space 3}0.002{col 77}{space 4} .0850651{col 90}{space 3} .5838023
{txt}{space 32}25  {c |}{col 37}{res}{space 2} 1.664553{col 49}{space 2} .2608049{col 60}{space 1}    3.25{col 69}{space 3}0.001{col 77}{space 4} 1.224419{col 90}{space 3}   2.2629
{txt}{space 32}26  {c |}{col 37}{res}{space 2} .7557889{col 49}{space 2} .1135969{col 60}{space 1}   -1.86{col 69}{space 3}0.062{col 77}{space 4}  .562941{col 90}{space 3} 1.014701
{txt}{space 32}27  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}28  {c |}{col 37}{res}{space 2} 1.623976{col 49}{space 2} .1497643{col 60}{space 1}    5.26{col 69}{space 3}0.000{col 77}{space 4} 1.355442{col 90}{space 3} 1.945709
{txt}{space 32}29  {c |}{col 37}{res}{space 2} 3.604171{col 49}{space 2} 1.122513{col 60}{space 1}    4.12{col 69}{space 3}0.000{col 77}{space 4} 1.957493{col 90}{space 3} 6.636064
{txt}{space 32}30  {c |}{col 37}{res}{space 2} 1.441261{col 49}{space 2} .3821374{col 60}{space 1}    1.38{col 69}{space 3}0.168{col 77}{space 4} .8571451{col 90}{space 3} 2.423433
{txt}{space 32}50  {c |}{col 37}{res}{space 2} 1.937842{col 49}{space 2}   .35103{col 60}{space 1}    3.65{col 69}{space 3}0.000{col 77}{space 4} 1.358713{col 90}{space 3} 2.763815
{txt}{space 32}51  {c |}{col 37}{res}{space 2} 3.977388{col 49}{space 2} .9559369{col 60}{space 1}    5.74{col 69}{space 3}0.000{col 77}{space 4} 2.483235{col 90}{space 3} 6.370568
{txt}{space 32}52  {c |}{col 37}{res}{space 2} 1.816186{col 49}{space 2} .5739898{col 60}{space 1}    1.89{col 69}{space 3}0.059{col 77}{space 4} .9775643{col 90}{space 3} 3.374233
{txt}{space 32}53  {c |}{col 37}{res}{space 2} 1.569846{col 49}{space 2} .1655984{col 60}{space 1}    4.28{col 69}{space 3}0.000{col 77}{space 4} 1.276634{col 90}{space 3} 1.930402
{txt}{space 32}54  {c |}{col 37}{res}{space 2} 1.735746{col 49}{space 2}  .324778{col 60}{space 1}    2.95{col 69}{space 3}0.003{col 77}{space 4} 1.202864{col 90}{space 3}   2.5047
{txt}{space 32}55  {c |}{col 37}{res}{space 2} 1.808186{col 49}{space 2} .5618116{col 60}{space 1}    1.91{col 69}{space 3}0.057{col 77}{space 4} .9834918{col 90}{space 3} 3.324415
{txt}{space 32}56  {c |}{col 37}{res}{space 2} 1.348479{col 49}{space 2}  .426355{col 60}{space 1}    0.95{col 69}{space 3}0.344{col 77}{space 4} .7256313{col 90}{space 3} 2.505952
{txt}{space 32}57  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}58  {c |}{col 37}{res}{space 2}  .952186{col 49}{space 2} .2758205{col 60}{space 1}   -0.17{col 69}{space 3}0.866{col 77}{space 4} .5397014{col 90}{space 3} 1.679926
{txt}{space 32}59  {c |}{col 37}{res}{space 2}  .328462{col 49}{space 2} .1155218{col 60}{space 1}   -3.17{col 69}{space 3}0.002{col 77}{space 4} .1648592{col 90}{space 3} .6544208
{txt}{space 32}60  {c |}{col 37}{res}{space 2} 1.044417{col 49}{space 2} .1457487{col 60}{space 1}    0.31{col 69}{space 3}0.755{col 77}{space 4} .7944902{col 90}{space 3} 1.372965
{txt}{space 32}61  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 35} {c |}
{space 29}reagan {c |}{col 37}{res}{space 2} .0714079{col 49}{space 2} .0705865{col 60}{space 1}   -2.67{col 69}{space 3}0.008{col 77}{space 4} .0102881{col 90}{space 3} .4956282
{txt}{space 29}bush41 {c |}{col 37}{res}{space 2} .1841843{col 49}{space 2} .1170026{col 60}{space 1}   -2.66{col 69}{space 3}0.008{col 77}{space 4} .0530309{col 90}{space 3} .6396998
{txt}{space 28}clinton {c |}{col 37}{res}{space 2} .6968965{col 49}{space 2} .3812339{col 60}{space 1}   -0.66{col 69}{space 3}0.509{col 77}{space 4} .2385187{col 90}{space 3}  2.03617
{txt}{space 29}bush43 {c |}{col 37}{res}{space 2} .2705098{col 49}{space 2} .2114258{col 60}{space 1}   -1.67{col 69}{space 3}0.094{col 77}{space 4} .0584653{col 90}{space 3} 1.251606
{txt}{hline 36}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-4793.444{col 39}-4482.609{col 50}    40{col 58} 9045.217{col 69} 9235.494
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.soubinaryagency2nom#c.zmecompmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.soubinaryagency2nom#c.zmecompmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.008109{col 26}{space 2} .1102907{col 37}{space 1}    0.07{col 46}{space 3}0.941{col 54}{space 4} .8135476{col 67}{space 3}   1.2492
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB11zmecom = r(table)
{txt}
{com}. mat list modelB11zmecom
{res}
{txt}modelB11zmecom[9,1]
              (1)
     b {res}  1.008109
{txt}    se {res} .11029073
{txt}     z {res} .07382083
{txt}pvalue {res} .94115295
{txt}    ll {res} .81354762
{txt}    ul {res}    1.2492
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. 
. **** MODEL B1.2: APPOINTEE MANAGERIAL COMPETENCE X POLICY PRIORITY AGENCY -- WEIBULL MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. 
. streg   zloyalmedian zpecompmedian  c.zmecompmedian##i.soubinaryagency2nom  toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign standaloneagencydesign okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment   i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-610.72149}  
Iteration 2:{space 3}log pseudolikelihood = {res:-510.39392}  
Iteration 3:{space 3}log pseudolikelihood = {res:-509.13996}  
Iteration 4:{space 3}log pseudolikelihood = {res:-509.13734}  
Iteration 5:{space 3}log pseudolikelihood = {res:-509.13734}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-509.13734             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 101:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 36}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 37}{c |}{col 49}    Robust
{col 1}                                 _t{col 37}{c |} Haz. Ratio{col 49}   Std. Err.{col 61}      z{col 69}   P>|z|{col 77}     [95% Con{col 90}f. Interval]
{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}zloyalmedian {c |}{col 37}{res}{space 2} .9976005{col 49}{space 2} .0768887{col 60}{space 1}   -0.03{col 69}{space 3}0.975{col 77}{space 4} .8577317{col 90}{space 3} 1.160277
{txt}{space 22}zpecompmedian {c |}{col 37}{res}{space 2}   1.0451{col 49}{space 2} .0814984{col 60}{space 1}    0.57{col 69}{space 3}0.572{col 77}{space 4} .8969738{col 90}{space 3} 1.217687
{txt}{space 22}zmecompmedian {c |}{col 37}{res}{space 2} .9797539{col 49}{space 2} .0855202{col 60}{space 1}   -0.23{col 69}{space 3}0.815{col 77}{space 4} .8256916{col 90}{space 3} 1.162562
{txt}{space 14}1.soubinaryagency2nom {c |}{col 37}{res}{space 2} 1.052772{col 49}{space 2} .1808883{col 60}{space 1}    0.30{col 69}{space 3}0.765{col 77}{space 4} .7517614{col 90}{space 3} 1.474309
{txt}{space 35} {c |}
soubinaryagency2nom#c.zmecompmedian {c |}
{space 33}1  {c |}{col 37}{res}{space 2}  .999029{col 49}{space 2} .0752532{col 60}{space 1}   -0.01{col 69}{space 3}0.990{col 77}{space 4} .8619067{col 90}{space 3} 1.157966
{txt}{space 35} {c |}
{space 26}toplevel2 {c |}{col 37}{res}{space 2} .5260741{col 49}{space 2} .0562241{col 60}{space 1}   -6.01{col 69}{space 3}0.000{col 77}{space 4} .4266531{col 90}{space 3} .6486627
{txt}{space 15}presagencyideolalign {c |}{col 37}{res}{space 2}  .713758{col 49}{space 2} .1667869{col 60}{space 1}   -1.44{col 69}{space 3}0.149{col 77}{space 4} .4514888{col 90}{space 3} 1.128379
{txt}{space 13}presagencyideolopposed {c |}{col 37}{res}{space 2} .6840489{col 49}{space 2} .1646124{col 60}{space 1}   -1.58{col 69}{space 3}0.115{col 77}{space 4} .4268256{col 90}{space 3} 1.096286
{txt}{space 20}subagencydesign {c |}{col 37}{res}{space 2} 1.425275{col 49}{space 2} .2223342{col 60}{space 1}    2.27{col 69}{space 3}0.023{col 77}{space 4} 1.049824{col 90}{space 3}    1.935
{txt}{space 13}standaloneagencydesign {c |}{col 37}{res}{space 2} 1.651648{col 49}{space 2} .3995688{col 60}{space 1}    2.07{col 69}{space 3}0.038{col 77}{space 4} 1.028002{col 90}{space 3} 2.653636
{txt}{space 9}okstartsenpolarizationmean {c |}{col 37}{res}{space 2} 2.94e-10{col 49}{space 2} 3.10e-09{col 60}{space 1}   -2.09{col 69}{space 3}0.037{col 77}{space 4} 3.25e-19{col 90}{space 3} .2663317
{txt}{space 12}okstartfilipresdistance {c |}{col 37}{res}{space 2} 457.8094{col 49}{space 2} 1071.113{col 60}{space 1}    2.62{col 69}{space 3}0.009{col 77}{space 4} 4.668445{col 90}{space 3} 44894.92
{txt}{space 24}okcrossover {c |}{col 37}{res}{space 2} .1794596{col 49}{space 2} .0397742{col 60}{space 1}   -7.75{col 69}{space 3}0.000{col 77}{space 4} .1162283{col 90}{space 3} .2770903
{txt}{space 21}okstartpresapp {c |}{col 37}{res}{space 2} .9925565{col 49}{space 2} .0047261{col 60}{space 1}   -1.57{col 69}{space 3}0.117{col 77}{space 4} .9833367{col 90}{space 3} 1.001863
{txt}{space 16}okstartunemployment {c |}{col 37}{res}{space 2} 1.119752{col 49}{space 2} .1069001{col 60}{space 1}    1.18{col 69}{space 3}0.236{col 77}{space 4} .9286658{col 90}{space 3} 1.350156
{txt}{space 35} {c |}
{space 24}okstartadyr {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 1.679815{col 49}{space 2} .3736961{col 60}{space 1}    2.33{col 69}{space 3}0.020{col 77}{space 4} 1.086178{col 90}{space 3} 2.597897
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 4.364597{col 49}{space 2} .9592203{col 60}{space 1}    6.70{col 69}{space 3}0.000{col 77}{space 4}  2.83709{col 90}{space 3} 6.714524
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 4.096428{col 49}{space 2} 1.259637{col 60}{space 1}    4.59{col 69}{space 3}0.000{col 77}{space 4} 2.242147{col 90}{space 3} 7.484223
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.528556{col 49}{space 2} .3913097{col 60}{space 1}    1.66{col 69}{space 3}0.097{col 77}{space 4} .9254949{col 90}{space 3} 2.524577
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 3.509461{col 49}{space 2} .9098971{col 60}{space 1}    4.84{col 69}{space 3}0.000{col 77}{space 4} 2.111298{col 90}{space 3} 5.833527
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 6.381411{col 49}{space 2} 1.930574{col 60}{space 1}    6.13{col 69}{space 3}0.000{col 77}{space 4} 3.526972{col 90}{space 3}   11.546
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 9.936952{col 49}{space 2}  3.90716{col 60}{space 1}    5.84{col 69}{space 3}0.000{col 77}{space 4} 4.597958{col 90}{space 3} 21.47541
{txt}{space 35} {c |}
{space 27}sbagency {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 2.551551{col 49}{space 2} .6230157{col 60}{space 1}    3.84{col 69}{space 3}0.000{col 77}{space 4} 1.581121{col 90}{space 3} 4.117592
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 1.780416{col 49}{space 2}  .393408{col 60}{space 1}    2.61{col 69}{space 3}0.009{col 77}{space 4} 1.154613{col 90}{space 3} 2.745405
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 1.412769{col 49}{space 2} .2742077{col 60}{space 1}    1.78{col 69}{space 3}0.075{col 77}{space 4} .9657386{col 90}{space 3} 2.066726
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.171114{col 49}{space 2} .2815717{col 60}{space 1}    0.66{col 69}{space 3}0.511{col 77}{space 4} .7310448{col 90}{space 3} 1.876092
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 2.643803{col 49}{space 2} .5648541{col 60}{space 1}    4.55{col 69}{space 3}0.000{col 77}{space 4} 1.739274{col 90}{space 3} 4.018742
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 1.796477{col 49}{space 2} .4571918{col 60}{space 1}    2.30{col 69}{space 3}0.021{col 77}{space 4} 1.090928{col 90}{space 3} 2.958332
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 2.268907{col 49}{space 2} .5248031{col 60}{space 1}    3.54{col 69}{space 3}0.000{col 77}{space 4} 1.441889{col 90}{space 3} 3.570273
{txt}{space 33}9  {c |}{col 37}{res}{space 2} 1.963103{col 49}{space 2} .4421225{col 60}{space 1}    3.00{col 69}{space 3}0.003{col 77}{space 4} 1.262521{col 90}{space 3} 3.052442
{txt}{space 32}11  {c |}{col 37}{res}{space 2} 3.287536{col 49}{space 2} .9709667{col 60}{space 1}    4.03{col 69}{space 3}0.000{col 77}{space 4} 1.842765{col 90}{space 3} 5.865041
{txt}{space 32}12  {c |}{col 37}{res}{space 2} 1.939095{col 49}{space 2} .3365307{col 60}{space 1}    3.82{col 69}{space 3}0.000{col 77}{space 4}  1.37998{col 90}{space 3} 2.724743
{txt}{space 32}13  {c |}{col 37}{res}{space 2} 1.492988{col 49}{space 2} .3075443{col 60}{space 1}    1.95{col 69}{space 3}0.052{col 77}{space 4} .9970459{col 90}{space 3} 2.235617
{txt}{space 32}14  {c |}{col 37}{res}{space 2} 2.251412{col 49}{space 2} .5356724{col 60}{space 1}    3.41{col 69}{space 3}0.001{col 77}{space 4} 1.412313{col 90}{space 3} 3.589046
{txt}{space 32}15  {c |}{col 37}{res}{space 2} 1.493054{col 49}{space 2} .3389954{col 60}{space 1}    1.77{col 69}{space 3}0.078{col 77}{space 4} .9567791{col 90}{space 3} 2.329911
{txt}{space 32}16  {c |}{col 37}{res}{space 2} .8379293{col 49}{space 2}  .135299{col 60}{space 1}   -1.10{col 69}{space 3}0.273{col 77}{space 4} .6106121{col 90}{space 3} 1.149872
{txt}{space 32}17  {c |}{col 37}{res}{space 2} 1.613189{col 49}{space 2}  .135852{col 60}{space 1}    5.68{col 69}{space 3}0.000{col 77}{space 4} 1.367738{col 90}{space 3} 1.902689
{txt}{space 32}18  {c |}{col 37}{res}{space 2} 1.898544{col 49}{space 2} .4672345{col 60}{space 1}    2.60{col 69}{space 3}0.009{col 77}{space 4}  1.17203{col 90}{space 3} 3.075407
{txt}{space 32}19  {c |}{col 37}{res}{space 2}  .723411{col 49}{space 2} .1083167{col 60}{space 1}   -2.16{col 69}{space 3}0.031{col 77}{space 4}  .539429{col 90}{space 3} .9701434
{txt}{space 32}20  {c |}{col 37}{res}{space 2} .3273187{col 49}{space 2} .0925948{col 60}{space 1}   -3.95{col 69}{space 3}0.000{col 77}{space 4} .1880075{col 90}{space 3} .5698576
{txt}{space 32}21  {c |}{col 37}{res}{space 2} .9457704{col 49}{space 2} .0931114{col 60}{space 1}   -0.57{col 69}{space 3}0.571{col 77}{space 4} .7798026{col 90}{space 3} 1.147062
{txt}{space 32}22  {c |}{col 37}{res}{space 2} .5755369{col 49}{space 2} .1941172{col 60}{space 1}   -1.64{col 69}{space 3}0.101{col 77}{space 4} .2971527{col 90}{space 3} 1.114722
{txt}{space 32}23  {c |}{col 37}{res}{space 2} 1.260318{col 49}{space 2} .2913502{col 60}{space 1}    1.00{col 69}{space 3}0.317{col 77}{space 4} .8011356{col 90}{space 3} 1.982686
{txt}{space 32}24  {c |}{col 37}{res}{space 2}   .24647{col 49}{space 2} .0974998{col 60}{space 1}   -3.54{col 69}{space 3}0.000{col 77}{space 4}  .113512{col 90}{space 3} .5351636
{txt}{space 32}25  {c |}{col 37}{res}{space 2} 1.752543{col 49}{space 2} .2895621{col 60}{space 1}    3.40{col 69}{space 3}0.001{col 77}{space 4} 1.267739{col 90}{space 3} 2.422745
{txt}{space 32}26  {c |}{col 37}{res}{space 2} .7617413{col 49}{space 2} .1287833{col 60}{space 1}   -1.61{col 69}{space 3}0.107{col 77}{space 4} .5468896{col 90}{space 3}    1.061
{txt}{space 32}27  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}28  {c |}{col 37}{res}{space 2}  1.45688{col 49}{space 2} .1367524{col 60}{space 1}    4.01{col 69}{space 3}0.000{col 77}{space 4} 1.212061{col 90}{space 3}  1.75115
{txt}{space 32}29  {c |}{col 37}{res}{space 2} 3.108769{col 49}{space 2}  .891208{col 60}{space 1}    3.96{col 69}{space 3}0.000{col 77}{space 4} 1.772433{col 90}{space 3} 5.452643
{txt}{space 32}30  {c |}{col 37}{res}{space 2} 1.291055{col 49}{space 2} .3382805{col 60}{space 1}    0.97{col 69}{space 3}0.330{col 77}{space 4} .7725275{col 90}{space 3} 2.157622
{txt}{space 32}50  {c |}{col 37}{res}{space 2} 1.773611{col 49}{space 2} .3085542{col 60}{space 1}    3.29{col 69}{space 3}0.001{col 77}{space 4} 1.261175{col 90}{space 3} 2.494259
{txt}{space 32}51  {c |}{col 37}{res}{space 2} 3.498087{col 49}{space 2} .7850418{col 60}{space 1}    5.58{col 69}{space 3}0.000{col 77}{space 4} 2.253221{col 90}{space 3} 5.430722
{txt}{space 32}52  {c |}{col 37}{res}{space 2}  1.82809{col 49}{space 2}  .563926{col 60}{space 1}    1.96{col 69}{space 3}0.051{col 77}{space 4} .9986662{col 90}{space 3} 3.346376
{txt}{space 32}53  {c |}{col 37}{res}{space 2} 1.532995{col 49}{space 2} .1705593{col 60}{space 1}    3.84{col 69}{space 3}0.000{col 77}{space 4} 1.232642{col 90}{space 3} 1.906534
{txt}{space 32}54  {c |}{col 37}{res}{space 2} 1.577226{col 49}{space 2} .2822135{col 60}{space 1}    2.55{col 69}{space 3}0.011{col 77}{space 4} 1.110678{col 90}{space 3} 2.239751
{txt}{space 32}55  {c |}{col 37}{res}{space 2} 1.513981{col 49}{space 2} .4415134{col 60}{space 1}    1.42{col 69}{space 3}0.155{col 77}{space 4} .8548493{col 90}{space 3} 2.681337
{txt}{space 32}56  {c |}{col 37}{res}{space 2} 1.281403{col 49}{space 2} .3912132{col 60}{space 1}    0.81{col 69}{space 3}0.417{col 77}{space 4} .7043903{col 90}{space 3} 2.331085
{txt}{space 32}57  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}58  {c |}{col 37}{res}{space 2} .7885093{col 49}{space 2} .2413431{col 60}{space 1}   -0.78{col 69}{space 3}0.438{col 77}{space 4} .4327881{col 90}{space 3} 1.436608
{txt}{space 32}59  {c |}{col 37}{res}{space 2} .3431799{col 49}{space 2}  .073285{col 60}{space 1}   -5.01{col 69}{space 3}0.000{col 77}{space 4} .2258139{col 90}{space 3} .5215467
{txt}{space 32}60  {c |}{col 37}{res}{space 2} .8917872{col 49}{space 2} .1246904{col 60}{space 1}   -0.82{col 69}{space 3}0.413{col 77}{space 4} .6780248{col 90}{space 3} 1.172943
{txt}{space 32}61  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 35} {c |}
{space 29}reagan {c |}{col 37}{res}{space 2} .0806433{col 49}{space 2} .0793517{col 60}{space 1}   -2.56{col 69}{space 3}0.011{col 77}{space 4}  .011722{col 90}{space 3} .5548002
{txt}{space 29}bush41 {c |}{col 37}{res}{space 2} .1892901{col 49}{space 2} .1194998{col 60}{space 1}   -2.64{col 69}{space 3}0.008{col 77}{space 4} .0549237{col 90}{space 3} .6523728
{txt}{space 28}clinton {c |}{col 37}{res}{space 2} .6681548{col 49}{space 2} .3692315{col 60}{space 1}   -0.73{col 69}{space 3}0.466{col 77}{space 4} .2261994{col 90}{space 3} 1.973617
{txt}{space 29}bush43 {c |}{col 37}{res}{space 2} .2741727{col 49}{space 2} .2129979{col 60}{space 1}   -1.67{col 69}{space 3}0.096{col 77}{space 4} .0598063{col 90}{space 3} 1.256901
{txt}{space 30}_cons {c |}{col 37}{res}{space 2} .0002693{col 49}{space 2} .0014711{col 60}{space 1}   -1.50{col 69}{space 3}0.132{col 77}{space 4} 6.04e-09{col 90}{space 3} 12.00702
{txt}{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 30}/ln_p {c |}{col 37}{res}{space 2} .9745685{col 49}{space 2} .0312909{col 60}{space 1}   31.15{col 69}{space 3}0.000{col 77}{space 4} .9132394{col 90}{space 3} 1.035898
{txt}{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                                  p {c |}{col 37}{res}{space 2} 2.650023{col 49}{space 2} .0829217{col 77}{space 4} 2.492383{col 90}{space 3} 2.817634
{txt}                                1/p {c |}{col 37}{res}{space 2} .3773552{col 49}{space 2} .0118078{col 77}{space 4} .3549077{col 90}{space 3} .4012224
{txt}{hline 36}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-830.8551{col 39}-509.1373{col 50}    24{col 58} 1066.275{col 69} 1180.441
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.soubinaryagency2nom#c.zmecompmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.soubinaryagency2nom#c.zmecompmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .9986746{col 26}{space 2} .1027084{col 37}{space 1}   -0.01{col 46}{space 3}0.990{col 54}{space 4} .8163612{col 67}{space 3} 1.221703
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB12zmecom = r(table)
{txt}
{com}. mat list modelB12zmecom
{res}
{txt}modelB12zmecom[9,1]
              (1)
     b {res} .99867455
{txt}    se {res} .10270844
{txt}     z {res} -.0128964
{txt}pvalue {res} .98971045
{txt}    ll {res} .81636123
{txt}    ul {res} 1.2217029
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. ** Generate 'manual' interaction variable ** 
. generate zmecomppdiff = soubinaryagency2nom*zmecompmedian
{txt}
{com}. 
. ** Re-Estimate Model 3  with 'manual' interaction variable **
. streg   zloyalmedian soubinaryagency2nom zmecomppdiff  zpecompmedian  zmecompmedian   toplevel2   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i.okstartadyr i.sbagency reagan bush41 clinton bush43, distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-610.72149}  
Iteration 2:{space 3}log pseudolikelihood = {res:-510.39392}  
Iteration 3:{space 3}log pseudolikelihood = {res:-509.13996}  
Iteration 4:{space 3}log pseudolikelihood = {res:-509.13734}  
Iteration 5:{space 3}log pseudolikelihood = {res:-509.13734}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-509.13734             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} .9976005{col 40}{space 2} .0768887{col 51}{space 1}   -0.03{col 60}{space 3}0.975{col 68}{space 4} .8577317{col 81}{space 3} 1.160277
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.052772{col 40}{space 2} .1808883{col 51}{space 1}    0.30{col 60}{space 3}0.765{col 68}{space 4} .7517614{col 81}{space 3} 1.474309
{txt}{space 14}zmecomppdiff {c |}{col 28}{res}{space 2}  .999029{col 40}{space 2} .0752532{col 51}{space 1}   -0.01{col 60}{space 3}0.990{col 68}{space 4} .8619067{col 81}{space 3} 1.157966
{txt}{space 13}zpecompmedian {c |}{col 28}{res}{space 2}   1.0451{col 40}{space 2} .0814984{col 51}{space 1}    0.57{col 60}{space 3}0.572{col 68}{space 4} .8969738{col 81}{space 3} 1.217687
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9797539{col 40}{space 2} .0855202{col 51}{space 1}   -0.23{col 60}{space 3}0.815{col 68}{space 4} .8256916{col 81}{space 3} 1.162562
{txt}{space 17}toplevel2 {c |}{col 28}{res}{space 2} .5260741{col 40}{space 2} .0562241{col 51}{space 1}   -6.01{col 60}{space 3}0.000{col 68}{space 4} .4266531{col 81}{space 3} .6486627
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2}  .713758{col 40}{space 2} .1667869{col 51}{space 1}   -1.44{col 60}{space 3}0.149{col 68}{space 4} .4514888{col 81}{space 3} 1.128379
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .6840489{col 40}{space 2} .1646124{col 51}{space 1}   -1.58{col 60}{space 3}0.115{col 68}{space 4} .4268256{col 81}{space 3} 1.096286
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.425275{col 40}{space 2} .2223342{col 51}{space 1}    2.27{col 60}{space 3}0.023{col 68}{space 4} 1.049824{col 81}{space 3}    1.935
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.651648{col 40}{space 2} .3995688{col 51}{space 1}    2.07{col 60}{space 3}0.038{col 68}{space 4} 1.028002{col 81}{space 3} 2.653636
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 2.94e-10{col 40}{space 2} 3.10e-09{col 51}{space 1}   -2.09{col 60}{space 3}0.037{col 68}{space 4} 3.25e-19{col 81}{space 3} .2663317
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 457.8094{col 40}{space 2} 1071.113{col 51}{space 1}    2.62{col 60}{space 3}0.009{col 68}{space 4} 4.668445{col 81}{space 3} 44894.92
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1794596{col 40}{space 2} .0397742{col 51}{space 1}   -7.75{col 60}{space 3}0.000{col 68}{space 4} .1162283{col 81}{space 3} .2770903
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9925565{col 40}{space 2} .0047261{col 51}{space 1}   -1.57{col 60}{space 3}0.117{col 68}{space 4} .9833367{col 81}{space 3} 1.001863
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.119752{col 40}{space 2} .1069001{col 51}{space 1}    1.18{col 60}{space 3}0.236{col 68}{space 4} .9286658{col 81}{space 3} 1.350156
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.679815{col 40}{space 2} .3736961{col 51}{space 1}    2.33{col 60}{space 3}0.020{col 68}{space 4} 1.086178{col 81}{space 3} 2.597897
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.364597{col 40}{space 2} .9592203{col 51}{space 1}    6.70{col 60}{space 3}0.000{col 68}{space 4}  2.83709{col 81}{space 3} 6.714524
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 4.096428{col 40}{space 2} 1.259637{col 51}{space 1}    4.59{col 60}{space 3}0.000{col 68}{space 4} 2.242147{col 81}{space 3} 7.484223
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.528556{col 40}{space 2} .3913097{col 51}{space 1}    1.66{col 60}{space 3}0.097{col 68}{space 4} .9254949{col 81}{space 3} 2.524577
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.509461{col 40}{space 2} .9098971{col 51}{space 1}    4.84{col 60}{space 3}0.000{col 68}{space 4} 2.111298{col 81}{space 3} 5.833527
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.381411{col 40}{space 2} 1.930574{col 51}{space 1}    6.13{col 60}{space 3}0.000{col 68}{space 4} 3.526972{col 81}{space 3}   11.546
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 9.936952{col 40}{space 2}  3.90716{col 51}{space 1}    5.84{col 60}{space 3}0.000{col 68}{space 4} 4.597958{col 81}{space 3} 21.47541
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 2.551551{col 40}{space 2} .6230157{col 51}{space 1}    3.84{col 60}{space 3}0.000{col 68}{space 4} 1.581121{col 81}{space 3} 4.117592
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.780416{col 40}{space 2}  .393408{col 51}{space 1}    2.61{col 60}{space 3}0.009{col 68}{space 4} 1.154613{col 81}{space 3} 2.745405
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.412769{col 40}{space 2} .2742077{col 51}{space 1}    1.78{col 60}{space 3}0.075{col 68}{space 4} .9657386{col 81}{space 3} 2.066726
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.171114{col 40}{space 2} .2815717{col 51}{space 1}    0.66{col 60}{space 3}0.511{col 68}{space 4} .7310448{col 81}{space 3} 1.876092
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 2.643803{col 40}{space 2} .5648541{col 51}{space 1}    4.55{col 60}{space 3}0.000{col 68}{space 4} 1.739274{col 81}{space 3} 4.018742
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.796477{col 40}{space 2} .4571918{col 51}{space 1}    2.30{col 60}{space 3}0.021{col 68}{space 4} 1.090928{col 81}{space 3} 2.958332
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.268907{col 40}{space 2} .5248031{col 51}{space 1}    3.54{col 60}{space 3}0.000{col 68}{space 4} 1.441889{col 81}{space 3} 3.570273
{txt}{space 24}9  {c |}{col 28}{res}{space 2} 1.963103{col 40}{space 2} .4421225{col 51}{space 1}    3.00{col 60}{space 3}0.003{col 68}{space 4} 1.262521{col 81}{space 3} 3.052442
{txt}{space 23}11  {c |}{col 28}{res}{space 2} 3.287536{col 40}{space 2} .9709667{col 51}{space 1}    4.03{col 60}{space 3}0.000{col 68}{space 4} 1.842765{col 81}{space 3} 5.865041
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 1.939095{col 40}{space 2} .3365307{col 51}{space 1}    3.82{col 60}{space 3}0.000{col 68}{space 4}  1.37998{col 81}{space 3} 2.724743
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.492988{col 40}{space 2} .3075443{col 51}{space 1}    1.95{col 60}{space 3}0.052{col 68}{space 4} .9970459{col 81}{space 3} 2.235617
{txt}{space 23}14  {c |}{col 28}{res}{space 2} 2.251412{col 40}{space 2} .5356724{col 51}{space 1}    3.41{col 60}{space 3}0.001{col 68}{space 4} 1.412313{col 81}{space 3} 3.589046
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.493054{col 40}{space 2} .3389954{col 51}{space 1}    1.77{col 60}{space 3}0.078{col 68}{space 4} .9567791{col 81}{space 3} 2.329911
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8379293{col 40}{space 2}  .135299{col 51}{space 1}   -1.10{col 60}{space 3}0.273{col 68}{space 4} .6106121{col 81}{space 3} 1.149872
{txt}{space 23}17  {c |}{col 28}{res}{space 2} 1.613189{col 40}{space 2}  .135852{col 51}{space 1}    5.68{col 60}{space 3}0.000{col 68}{space 4} 1.367738{col 81}{space 3} 1.902689
{txt}{space 23}18  {c |}{col 28}{res}{space 2} 1.898544{col 40}{space 2} .4672345{col 51}{space 1}    2.60{col 60}{space 3}0.009{col 68}{space 4}  1.17203{col 81}{space 3} 3.075407
{txt}{space 23}19  {c |}{col 28}{res}{space 2}  .723411{col 40}{space 2} .1083167{col 51}{space 1}   -2.16{col 60}{space 3}0.031{col 68}{space 4}  .539429{col 81}{space 3} .9701434
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .3273187{col 40}{space 2} .0925948{col 51}{space 1}   -3.95{col 60}{space 3}0.000{col 68}{space 4} .1880075{col 81}{space 3} .5698576
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .9457704{col 40}{space 2} .0931114{col 51}{space 1}   -0.57{col 60}{space 3}0.571{col 68}{space 4} .7798026{col 81}{space 3} 1.147062
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .5755369{col 40}{space 2} .1941172{col 51}{space 1}   -1.64{col 60}{space 3}0.101{col 68}{space 4} .2971527{col 81}{space 3} 1.114722
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.260318{col 40}{space 2} .2913502{col 51}{space 1}    1.00{col 60}{space 3}0.317{col 68}{space 4} .8011356{col 81}{space 3} 1.982686
{txt}{space 23}24  {c |}{col 28}{res}{space 2}   .24647{col 40}{space 2} .0974998{col 51}{space 1}   -3.54{col 60}{space 3}0.000{col 68}{space 4}  .113512{col 81}{space 3} .5351636
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.752543{col 40}{space 2} .2895621{col 51}{space 1}    3.40{col 60}{space 3}0.001{col 68}{space 4} 1.267739{col 81}{space 3} 2.422745
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .7617413{col 40}{space 2} .1287833{col 51}{space 1}   -1.61{col 60}{space 3}0.107{col 68}{space 4} .5468896{col 81}{space 3}    1.061
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2}  1.45688{col 40}{space 2} .1367524{col 51}{space 1}    4.01{col 60}{space 3}0.000{col 68}{space 4} 1.212061{col 81}{space 3}  1.75115
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 3.108769{col 40}{space 2}  .891208{col 51}{space 1}    3.96{col 60}{space 3}0.000{col 68}{space 4} 1.772433{col 81}{space 3} 5.452643
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.291055{col 40}{space 2} .3382805{col 51}{space 1}    0.97{col 60}{space 3}0.330{col 68}{space 4} .7725275{col 81}{space 3} 2.157622
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 1.773611{col 40}{space 2} .3085542{col 51}{space 1}    3.29{col 60}{space 3}0.001{col 68}{space 4} 1.261175{col 81}{space 3} 2.494259
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 3.498087{col 40}{space 2} .7850418{col 51}{space 1}    5.58{col 60}{space 3}0.000{col 68}{space 4} 2.253221{col 81}{space 3} 5.430722
{txt}{space 23}52  {c |}{col 28}{res}{space 2}  1.82809{col 40}{space 2}  .563926{col 51}{space 1}    1.96{col 60}{space 3}0.051{col 68}{space 4} .9986662{col 81}{space 3} 3.346376
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.532995{col 40}{space 2} .1705593{col 51}{space 1}    3.84{col 60}{space 3}0.000{col 68}{space 4} 1.232642{col 81}{space 3} 1.906534
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.577226{col 40}{space 2} .2822135{col 51}{space 1}    2.55{col 60}{space 3}0.011{col 68}{space 4} 1.110678{col 81}{space 3} 2.239751
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.513981{col 40}{space 2} .4415134{col 51}{space 1}    1.42{col 60}{space 3}0.155{col 68}{space 4} .8548493{col 81}{space 3} 2.681337
{txt}{space 23}56  {c |}{col 28}{res}{space 2} 1.281403{col 40}{space 2} .3912132{col 51}{space 1}    0.81{col 60}{space 3}0.417{col 68}{space 4} .7043903{col 81}{space 3} 2.331085
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} .7885093{col 40}{space 2} .2413431{col 51}{space 1}   -0.78{col 60}{space 3}0.438{col 68}{space 4} .4327881{col 81}{space 3} 1.436608
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3431799{col 40}{space 2}  .073285{col 51}{space 1}   -5.01{col 60}{space 3}0.000{col 68}{space 4} .2258139{col 81}{space 3} .5215467
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .8917872{col 40}{space 2} .1246904{col 51}{space 1}   -0.82{col 60}{space 3}0.413{col 68}{space 4} .6780248{col 81}{space 3} 1.172943
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0806433{col 40}{space 2} .0793517{col 51}{space 1}   -2.56{col 60}{space 3}0.011{col 68}{space 4}  .011722{col 81}{space 3} .5548002
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1892901{col 40}{space 2} .1194998{col 51}{space 1}   -2.64{col 60}{space 3}0.008{col 68}{space 4} .0549237{col 81}{space 3} .6523728
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6681548{col 40}{space 2} .3692315{col 51}{space 1}   -0.73{col 60}{space 3}0.466{col 68}{space 4} .2261994{col 81}{space 3} 1.973617
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2741727{col 40}{space 2} .2129979{col 51}{space 1}   -1.67{col 60}{space 3}0.096{col 68}{space 4} .0598063{col 81}{space 3} 1.256901
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .0002693{col 40}{space 2} .0014711{col 51}{space 1}   -1.50{col 60}{space 3}0.132{col 68}{space 4} 6.04e-09{col 81}{space 3} 12.00702
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9745685{col 40}{space 2} .0312909{col 51}{space 1}   31.15{col 60}{space 3}0.000{col 68}{space 4} .9132394{col 81}{space 3} 1.035898
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.650023{col 40}{space 2} .0829217{col 68}{space 4} 2.492383{col 81}{space 3} 2.817634
{txt}                       1/p {c |}{col 28}{res}{space 2} .3773552{col 40}{space 2} .0118078{col 68}{space 4} .3549077{col 81}{space 3} .4012224
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimate store modelb12a
{txt}
{com}. 
. 
. margins, predict(median time) at(zmecomppdiff=(-0.3960373 0.9692858))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1000.138{col 26}{space 2} 19.82866{col 37}{space 1}   50.44{col 46}{space 3}0.000{col 54}{space 4} 961.2746{col 67}{space 3} 1039.002
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 1000.639{col 26}{space 2} 33.37104{col 37}{space 1}   29.99{col 46}{space 3}0.000{col 54}{space 4} 935.2327{col 67}{space 3} 1066.045
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(zmecomppdiff=(-0.3960373 0.9692858))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     0.00{col 38}{space 2}   0.9897
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2} .5006908{col 26}{space 2} 38.82638{col 37}{space 5}-75.59761{col 51}{space 3}   76.599
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix modelB12azmecom = r(table)
{txt}
{com}. mat list modelB12azmecom
{res}
{txt}modelB12azmecom[9,1]
             r2vs1.
               _at
     b {res}  .50069082
{txt}    se {res}  38.826379
{txt}     z {res}  .01289564
{txt}pvalue {res}  .98971106
{txt}    ll {res} -75.597614
{txt}    ul {res}  76.598995
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. 
. estimates restore modelb12a
{txt}(results {stata estimates replay modelb12a:modelb12a} are active now)

{com}. 
. margins, predict(median time) at(zmecomppdiff=(-0.6451644 1.711348))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1000.047{col 26}{space 2}  24.2246{col 37}{space 1}   41.28{col 46}{space 3}0.000{col 54}{space 4} 952.5674{col 67}{space 3} 1047.526
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 1000.911{col 26}{space 2} 52.64467{col 37}{space 1}   19.01{col 46}{space 3}0.000{col 54}{space 4} 897.7293{col 67}{space 3} 1104.093
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, predict(median time) at(zmecomppdiff=(-0.6451644 1.711348))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zmecomppdiff}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     0.00{col 38}{space 2}   0.9897
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2} .8642575{col 26}{space 2} 67.02545{col 37}{space 5}-130.5032{col 51}{space 3} 132.2317
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix modelB12bzmecom = r(table)
{txt}
{com}. mat list modelB12bzmecom
{res}
{txt}modelB12bzmecom[9,1]
            r2vs1.
              _at
     b {res} .86425753
{txt}    se {res} 67.025445
{txt}     z {res} .01289447
{txt}pvalue {res} .98971199
{txt}    ll {res} -130.5032
{txt}    ul {res} 132.23172
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         0
{reset}
{com}. 
. 
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. 
. 
. 
. 
. **** ALTERNATIVE MECHANISM B2: DOES POLICY PRIORITY DISTINCTION HAVE A DIFFERENTIAL EFFECT OF APPOINTEE POLICY COMPETENCE ON APPOINTEE TENURE? ***
. 
. 
. 
. 
. **** MODEL B2.1:  APPOINTEE POLICY COMPETENCE X POLICY PRIORITY AGENCY -- COX MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. stcox   zloyalmedian c.zpecompmedian##i.soubinaryagency2nom  zmecompmedian  toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign  standaloneagencydesign okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur

{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
Iteration 0:   log pseudolikelihood = {res}-4793.4442
{txt}Iteration 1:   log pseudolikelihood = {res}-4506.8847
{txt}Iteration 2:   log pseudolikelihood = {res}-4479.7142
{txt}Iteration 3:   log pseudolikelihood = {res}-4479.3502
{txt}Iteration 4:   log pseudolikelihood = {res}-4479.3499
{txt}Refining estimates:
Iteration 0:   log pseudolikelihood = {res}-4479.3499

{txt}Cox regression -- Breslow method for ties

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
                                                {txt}Wald chi2({res}40{txt})    =  {res}  33193.02
{txt}Log pseudolikelihood =   {res}-4479.3499             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 101:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 36}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 37}{c |}{col 49}    Robust
{col 1}                                 _t{col 37}{c |} Haz. Ratio{col 49}   Std. Err.{col 61}      z{col 69}   P>|z|{col 77}     [95% Con{col 90}f. Interval]
{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}zloyalmedian {c |}{col 37}{res}{space 2} .9927865{col 49}{space 2} .0721407{col 60}{space 1}   -0.10{col 69}{space 3}0.921{col 77}{space 4} .8610006{col 90}{space 3} 1.144744
{txt}{space 22}zpecompmedian {c |}{col 37}{res}{space 2} .8873074{col 49}{space 2} .0922283{col 60}{space 1}   -1.15{col 69}{space 3}0.250{col 77}{space 4}  .723767{col 90}{space 3} 1.087801
{txt}{space 14}1.soubinaryagency2nom {c |}{col 37}{res}{space 2} 1.058478{col 49}{space 2} .1852977{col 60}{space 1}    0.32{col 69}{space 3}0.745{col 77}{space 4} .7510517{col 90}{space 3} 1.491741
{txt}{space 35} {c |}
soubinaryagency2nom#c.zpecompmedian {c |}
{space 33}1  {c |}{col 37}{res}{space 2}  1.25098{col 49}{space 2} .1253238{col 60}{space 1}    2.24{col 69}{space 3}0.025{col 77}{space 4} 1.027961{col 90}{space 3} 1.522384
{txt}{space 35} {c |}
{space 22}zmecompmedian {c |}{col 37}{res}{space 2} .9878648{col 49}{space 2} .0649016{col 60}{space 1}   -0.19{col 69}{space 3}0.853{col 77}{space 4} .8685094{col 90}{space 3} 1.123623
{txt}{space 26}toplevel2 {c |}{col 37}{res}{space 2} .5110583{col 49}{space 2} .0551289{col 60}{space 1}   -6.22{col 69}{space 3}0.000{col 77}{space 4} .4136659{col 90}{space 3} .6313806
{txt}{space 15}presagencyideolalign {c |}{col 37}{res}{space 2} .6849711{col 49}{space 2} .1698063{col 60}{space 1}   -1.53{col 69}{space 3}0.127{col 77}{space 4} .4213635{col 90}{space 3} 1.113493
{txt}{space 13}presagencyideolopposed {c |}{col 37}{res}{space 2} .6643003{col 49}{space 2} .1695369{col 60}{space 1}   -1.60{col 69}{space 3}0.109{col 77}{space 4}  .402836{col 90}{space 3} 1.095471
{txt}{space 20}subagencydesign {c |}{col 37}{res}{space 2} 1.535336{col 49}{space 2} .2668774{col 60}{space 1}    2.47{col 69}{space 3}0.014{col 77}{space 4} 1.092055{col 90}{space 3}  2.15855
{txt}{space 13}standaloneagencydesign {c |}{col 37}{res}{space 2} 1.895722{col 49}{space 2} .5147062{col 60}{space 1}    2.36{col 69}{space 3}0.018{col 77}{space 4} 1.113437{col 90}{space 3} 3.227631
{txt}{space 9}okstartsenpolarizationmean {c |}{col 37}{res}{space 2} 1.68e-11{col 49}{space 2} 1.77e-10{col 60}{space 1}   -2.35{col 69}{space 3}0.019{col 77}{space 4} 1.77e-20{col 90}{space 3} .0159236
{txt}{space 12}okstartfilipresdistance {c |}{col 37}{res}{space 2} 731.7865{col 49}{space 2} 1699.032{col 60}{space 1}    2.84{col 69}{space 3}0.005{col 77}{space 4} 7.728584{col 90}{space 3} 69289.73
{txt}{space 24}okcrossover {c |}{col 37}{res}{space 2} .1700102{col 49}{space 2} .0377215{col 60}{space 1}   -7.99{col 69}{space 3}0.000{col 77}{space 4} .1100556{col 90}{space 3} .2626262
{txt}{space 21}okstartpresapp {c |}{col 37}{res}{space 2} .9918954{col 49}{space 2} .0045605{col 60}{space 1}   -1.77{col 69}{space 3}0.077{col 77}{space 4}  .982997{col 90}{space 3} 1.000874
{txt}{space 16}okstartunemployment {c |}{col 37}{res}{space 2} 1.141599{col 49}{space 2} .1033408{col 60}{space 1}    1.46{col 69}{space 3}0.143{col 77}{space 4} .9560055{col 90}{space 3} 1.363223
{txt}{space 35} {c |}
{space 24}okstartadyr {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 1.648446{col 49}{space 2} .3721941{col 60}{space 1}    2.21{col 69}{space 3}0.027{col 77}{space 4} 1.058976{col 90}{space 3} 2.566038
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 3.932745{col 49}{space 2}  .895081{col 60}{space 1}    6.02{col 69}{space 3}0.000{col 77}{space 4} 2.517473{col 90}{space 3} 6.143653
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 3.703517{col 49}{space 2} 1.213509{col 60}{space 1}    4.00{col 69}{space 3}0.000{col 77}{space 4} 1.948526{col 90}{space 3} 7.039187
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.676401{col 49}{space 2} .4203979{col 60}{space 1}    2.06{col 69}{space 3}0.039{col 77}{space 4}  1.02546{col 90}{space 3} 2.740547
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 3.833988{col 49}{space 2} .9668839{col 60}{space 1}    5.33{col 69}{space 3}0.000{col 77}{space 4} 2.338774{col 90}{space 3} 6.285113
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 5.666151{col 49}{space 2} 1.757877{col 60}{space 1}    5.59{col 69}{space 3}0.000{col 77}{space 4} 3.084678{col 90}{space 3} 10.40798
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 9.294376{col 49}{space 2}  3.57624{col 60}{space 1}    5.79{col 69}{space 3}0.000{col 77}{space 4} 4.372194{col 90}{space 3} 19.75791
{txt}{space 35} {c |}
{space 27}sbagency {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 2.836704{col 49}{space 2} .7440772{col 60}{space 1}    3.97{col 69}{space 3}0.000{col 77}{space 4} 1.696449{col 90}{space 3} 4.743371
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 1.870616{col 49}{space 2} .4531669{col 60}{space 1}    2.59{col 69}{space 3}0.010{col 77}{space 4} 1.163527{col 90}{space 3} 3.007412
{txt}{space 33}4  {c |}{col 37}{res}{space 2}  1.41774{col 49}{space 2}  .313261{col 60}{space 1}    1.58{col 69}{space 3}0.114{col 77}{space 4} .9194258{col 90}{space 3} 2.186132
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.222552{col 49}{space 2} .3065133{col 60}{space 1}    0.80{col 69}{space 3}0.423{col 77}{space 4} .7479241{col 90}{space 3} 1.998376
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 2.765675{col 49}{space 2} .6339504{col 60}{space 1}    4.44{col 69}{space 3}0.000{col 77}{space 4} 1.764769{col 90}{space 3} 4.334253
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 1.951959{col 49}{space 2} .5247976{col 60}{space 1}    2.49{col 69}{space 3}0.013{col 77}{space 4} 1.152443{col 90}{space 3} 3.306147
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 2.433604{col 49}{space 2} .6276876{col 60}{space 1}    3.45{col 69}{space 3}0.001{col 77}{space 4} 1.467924{col 90}{space 3}  4.03456
{txt}{space 33}9  {c |}{col 37}{res}{space 2} 2.114731{col 49}{space 2} .5158981{col 60}{space 1}    3.07{col 69}{space 3}0.002{col 77}{space 4} 1.310994{col 90}{space 3} 3.411218
{txt}{space 32}11  {c |}{col 37}{res}{space 2}  3.41484{col 49}{space 2} 1.106634{col 60}{space 1}    3.79{col 69}{space 3}0.000{col 77}{space 4} 1.809359{col 90}{space 3} 6.444897
{txt}{space 32}12  {c |}{col 37}{res}{space 2} 1.902363{col 49}{space 2} .3587928{col 60}{space 1}    3.41{col 69}{space 3}0.001{col 77}{space 4} 1.314479{col 90}{space 3} 2.753171
{txt}{space 32}13  {c |}{col 37}{res}{space 2} 1.506886{col 49}{space 2} .3448279{col 60}{space 1}    1.79{col 69}{space 3}0.073{col 77}{space 4} .9622676{col 90}{space 3} 2.359744
{txt}{space 32}14  {c |}{col 37}{res}{space 2} 2.502001{col 49}{space 2} .6536378{col 60}{space 1}    3.51{col 69}{space 3}0.000{col 77}{space 4} 1.499389{col 90}{space 3} 4.175038
{txt}{space 32}15  {c |}{col 37}{res}{space 2} 1.590184{col 49}{space 2} .3903547{col 60}{space 1}    1.89{col 69}{space 3}0.059{col 77}{space 4} .9828709{col 90}{space 3} 2.572755
{txt}{space 32}16  {c |}{col 37}{res}{space 2} .8445369{col 49}{space 2} .1317177{col 60}{space 1}   -1.08{col 69}{space 3}0.279{col 77}{space 4} .6221019{col 90}{space 3} 1.146505
{txt}{space 32}17  {c |}{col 37}{res}{space 2} 1.627549{col 49}{space 2} .1358429{col 60}{space 1}    5.84{col 69}{space 3}0.000{col 77}{space 4} 1.381938{col 90}{space 3} 1.916811
{txt}{space 32}18  {c |}{col 37}{res}{space 2} 2.019904{col 49}{space 2}  .552964{col 60}{space 1}    2.57{col 69}{space 3}0.010{col 77}{space 4} 1.181158{col 90}{space 3} 3.454248
{txt}{space 32}19  {c |}{col 37}{res}{space 2}  .694684{col 49}{space 2}  .104741{col 60}{space 1}   -2.42{col 69}{space 3}0.016{col 77}{space 4} .5169485{col 90}{space 3} .9335279
{txt}{space 32}20  {c |}{col 37}{res}{space 2} .2775439{col 49}{space 2}  .085688{col 60}{space 1}   -4.15{col 69}{space 3}0.000{col 77}{space 4} .1515425{col 90}{space 3} .5083103
{txt}{space 32}21  {c |}{col 37}{res}{space 2} .8365257{col 49}{space 2} .0838899{col 60}{space 1}   -1.78{col 69}{space 3}0.075{col 77}{space 4} .6872547{col 90}{space 3} 1.018218
{txt}{space 32}22  {c |}{col 37}{res}{space 2} .4326325{col 49}{space 2} .1462729{col 60}{space 1}   -2.48{col 69}{space 3}0.013{col 77}{space 4}  .223012{col 90}{space 3} .8392862
{txt}{space 32}23  {c |}{col 37}{res}{space 2} 1.019418{col 49}{space 2}  .241784{col 60}{space 1}    0.08{col 69}{space 3}0.935{col 77}{space 4} .6404208{col 90}{space 3} 1.622702
{txt}{space 32}24  {c |}{col 37}{res}{space 2} .2604279{col 49}{space 2} .1334928{col 60}{space 1}   -2.62{col 69}{space 3}0.009{col 77}{space 4} .0953609{col 90}{space 3} .7112218
{txt}{space 32}25  {c |}{col 37}{res}{space 2} 1.339289{col 49}{space 2} .2133247{col 60}{space 1}    1.83{col 69}{space 3}0.067{col 77}{space 4} .9801511{col 90}{space 3} 1.830018
{txt}{space 32}26  {c |}{col 37}{res}{space 2} .7927415{col 49}{space 2} .1123151{col 60}{space 1}   -1.64{col 69}{space 3}0.101{col 77}{space 4} .6005288{col 90}{space 3} 1.046476
{txt}{space 32}27  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}28  {c |}{col 37}{res}{space 2}  1.59162{col 49}{space 2} .1460159{col 60}{space 1}    5.07{col 69}{space 3}0.000{col 77}{space 4} 1.329689{col 90}{space 3} 1.905149
{txt}{space 32}29  {c |}{col 37}{res}{space 2} 3.347686{col 49}{space 2} 1.100842{col 60}{space 1}    3.67{col 69}{space 3}0.000{col 77}{space 4}  1.75727{col 90}{space 3} 6.377507
{txt}{space 32}30  {c |}{col 37}{res}{space 2} 1.424032{col 49}{space 2} .3939551{col 60}{space 1}    1.28{col 69}{space 3}0.201{col 77}{space 4} .8280123{col 90}{space 3} 2.449078
{txt}{space 32}50  {c |}{col 37}{res}{space 2} 1.777512{col 49}{space 2}  .315229{col 60}{space 1}    3.24{col 69}{space 3}0.001{col 77}{space 4}  1.25562{col 90}{space 3} 2.516327
{txt}{space 32}51  {c |}{col 37}{res}{space 2} 3.525203{col 49}{space 2} .9311787{col 60}{space 1}    4.77{col 69}{space 3}0.000{col 77}{space 4} 2.100585{col 90}{space 3}    5.916
{txt}{space 32}52  {c |}{col 37}{res}{space 2} 1.604459{col 49}{space 2} .5450724{col 60}{space 1}    1.39{col 69}{space 3}0.164{col 77}{space 4} .8244335{col 90}{space 3} 3.122495
{txt}{space 32}53  {c |}{col 37}{res}{space 2} 1.497505{col 49}{space 2} .1610709{col 60}{space 1}    3.75{col 69}{space 3}0.000{col 77}{space 4} 1.212868{col 90}{space 3} 1.848941
{txt}{space 32}54  {c |}{col 37}{res}{space 2} 1.554785{col 49}{space 2} .2861572{col 60}{space 1}    2.40{col 69}{space 3}0.016{col 77}{space 4} 1.083945{col 90}{space 3} 2.230147
{txt}{space 32}55  {c |}{col 37}{res}{space 2} 1.613997{col 49}{space 2} .5200591{col 60}{space 1}    1.49{col 69}{space 3}0.137{col 77}{space 4} .8582822{col 90}{space 3} 3.035116
{txt}{space 32}56  {c |}{col 37}{res}{space 2} 1.203026{col 49}{space 2} .4041139{col 60}{space 1}    0.55{col 69}{space 3}0.582{col 77}{space 4} .6227937{col 90}{space 3} 2.323839
{txt}{space 32}57  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}58  {c |}{col 37}{res}{space 2} 1.006171{col 49}{space 2} .2773577{col 60}{space 1}    0.02{col 69}{space 3}0.982{col 77}{space 4} .5861817{col 90}{space 3} 1.727075
{txt}{space 32}59  {c |}{col 37}{res}{space 2} .3633521{col 49}{space 2} .1284316{col 60}{space 1}   -2.86{col 69}{space 3}0.004{col 77}{space 4} .1817437{col 90}{space 3} .7264338
{txt}{space 32}60  {c |}{col 37}{res}{space 2} 1.019243{col 49}{space 2} .1399066{col 60}{space 1}    0.14{col 69}{space 3}0.890{col 77}{space 4} .7788206{col 90}{space 3} 1.333884
{txt}{space 32}61  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 35} {c |}
{space 29}reagan {c |}{col 37}{res}{space 2} .0686424{col 49}{space 2}  .067128{col 60}{space 1}   -2.74{col 69}{space 3}0.006{col 77}{space 4} .0100965{col 90}{space 3} .4666758
{txt}{space 29}bush41 {c |}{col 37}{res}{space 2} .1836192{col 49}{space 2} .1149989{col 60}{space 1}   -2.71{col 69}{space 3}0.007{col 77}{space 4} .0538045{col 90}{space 3}  .626639
{txt}{space 28}clinton {c |}{col 37}{res}{space 2} .7490836{col 49}{space 2} .4006553{col 60}{space 1}   -0.54{col 69}{space 3}0.589{col 77}{space 4} .2625767{col 90}{space 3}    2.137
{txt}{space 29}bush43 {c |}{col 37}{res}{space 2} .2780494{col 49}{space 2} .2121989{col 60}{space 1}   -1.68{col 69}{space 3}0.094{col 77}{space 4} .0623032{col 90}{space 3}  1.24089
{txt}{hline 36}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-4793.444{col 39} -4479.35{col 50}    40{col 58}   9038.7{col 69} 9228.977
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.soubinaryagency2nom#c.zpecompmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.soubinaryagency2nom#c.zpecompmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  1.35762{col 26}{space 2} .1856936{col 37}{space 1}    2.24{col 46}{space 3}0.025{col 54}{space 4} 1.038369{col 67}{space 3} 1.775025
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB21zpecom = r(table)
{txt}
{com}. mat list modelB21zpecom
{res}
{txt}modelB21zpecom[9,1]
              (1)
     b {res} 1.3576195
{txt}    se {res} .18569357
{txt}     z {res} 2.2352354
{txt}pvalue {res}  .0254019
{txt}    ll {res} 1.0383691
{txt}    ul {res} 1.7750247
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. 
. 
. 
. 
. **** MODEL B2.2: APPOINTEE POLICY COMPETENCE X POLICY PRIORITY AGENCY -- WEIBULL MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. streg   zloyalmedian c.zpecompmedian##i.soubinaryagency2nom  zmecompmedian   toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign standaloneagencydesign okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-611.75071}  
Iteration 2:{space 3}log pseudolikelihood = {res:-507.48169}  
Iteration 3:{space 3}log pseudolikelihood = {res:-506.15596}  
Iteration 4:{space 3}log pseudolikelihood = {res: -506.1528}  
Iteration 5:{space 3}log pseudolikelihood = {res: -506.1528}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res} -506.1528             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 101:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 36}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 37}{c |}{col 49}    Robust
{col 1}                                 _t{col 37}{c |} Haz. Ratio{col 49}   Std. Err.{col 61}      z{col 69}   P>|z|{col 77}     [95% Con{col 90}f. Interval]
{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}zloyalmedian {c |}{col 37}{res}{space 2} .9963408{col 49}{space 2} .0737671{col 60}{space 1}   -0.05{col 69}{space 3}0.961{col 77}{space 4} .8617606{col 90}{space 3} 1.151938
{txt}{space 22}zpecompmedian {c |}{col 37}{res}{space 2} .9031864{col 49}{space 2} .0856467{col 60}{space 1}   -1.07{col 69}{space 3}0.283{col 77}{space 4} .7499983{col 90}{space 3} 1.087663
{txt}{space 14}1.soubinaryagency2nom {c |}{col 37}{res}{space 2} 1.062304{col 49}{space 2} .1906042{col 60}{space 1}    0.34{col 69}{space 3}0.736{col 77}{space 4} .7473456{col 90}{space 3} 1.509996
{txt}{space 35} {c |}
soubinaryagency2nom#c.zpecompmedian {c |}
{space 33}1  {c |}{col 37}{res}{space 2} 1.237288{col 49}{space 2} .1172029{col 60}{space 1}    2.25{col 69}{space 3}0.025{col 77}{space 4} 1.027638{col 90}{space 3} 1.489709
{txt}{space 35} {c |}
{space 22}zmecompmedian {c |}{col 37}{res}{space 2} .9906859{col 49}{space 2} .0635315{col 60}{space 1}   -0.15{col 69}{space 3}0.884{col 77}{space 4} .8736741{col 90}{space 3} 1.123369
{txt}{space 26}toplevel2 {c |}{col 37}{res}{space 2} .5369567{col 49}{space 2} .0564068{col 60}{space 1}   -5.92{col 69}{space 3}0.000{col 77}{space 4} .4370401{col 90}{space 3} .6597164
{txt}{space 15}presagencyideolalign {c |}{col 37}{res}{space 2} .7657247{col 49}{space 2} .1781615{col 60}{space 1}   -1.15{col 69}{space 3}0.251{col 77}{space 4} .4853144{col 90}{space 3} 1.208154
{txt}{space 13}presagencyideolopposed {c |}{col 37}{res}{space 2} .7337904{col 49}{space 2} .1755976{col 60}{space 1}   -1.29{col 69}{space 3}0.196{col 77}{space 4} .4590687{col 90}{space 3} 1.172914
{txt}{space 20}subagencydesign {c |}{col 37}{res}{space 2} 1.487826{col 49}{space 2} .2519738{col 60}{space 1}    2.35{col 69}{space 3}0.019{col 77}{space 4} 1.067567{col 90}{space 3} 2.073524
{txt}{space 13}standaloneagencydesign {c |}{col 37}{res}{space 2} 1.623201{col 49}{space 2} .4180759{col 60}{space 1}    1.88{col 69}{space 3}0.060{col 77}{space 4} .9797932{col 90}{space 3} 2.689119
{txt}{space 9}okstartsenpolarizationmean {c |}{col 37}{res}{space 2} 9.01e-11{col 49}{space 2} 9.47e-10{col 60}{space 1}   -2.20{col 69}{space 3}0.028{col 77}{space 4} 1.00e-19{col 90}{space 3} .0810311
{txt}{space 12}okstartfilipresdistance {c |}{col 37}{res}{space 2} 559.9089{col 49}{space 2} 1297.626{col 60}{space 1}    2.73{col 69}{space 3}0.006{col 77}{space 4} 5.962133{col 90}{space 3} 52581.52
{txt}{space 24}okcrossover {c |}{col 37}{res}{space 2} .1797963{col 49}{space 2} .0392101{col 60}{space 1}   -7.87{col 69}{space 3}0.000{col 77}{space 4} .1172601{col 90}{space 3} .2756838
{txt}{space 21}okstartpresapp {c |}{col 37}{res}{space 2} .9924446{col 49}{space 2} .0046382{col 60}{space 1}   -1.62{col 69}{space 3}0.105{col 77}{space 4} .9833954{col 90}{space 3} 1.001577
{txt}{space 16}okstartunemployment {c |}{col 37}{res}{space 2} 1.130397{col 49}{space 2} .1039524{col 60}{space 1}    1.33{col 69}{space 3}0.183{col 77}{space 4} .9439604{col 90}{space 3} 1.353656
{txt}{space 35} {c |}
{space 24}okstartadyr {c |}
{space 33}2  {c |}{col 37}{res}{space 2} 1.677727{col 49}{space 2} .3732354{col 60}{space 1}    2.33{col 69}{space 3}0.020{col 77}{space 4} 1.084823{col 90}{space 3}  2.59468
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 4.379084{col 49}{space 2} .9467543{col 60}{space 1}    6.83{col 69}{space 3}0.000{col 77}{space 4} 2.866515{col 90}{space 3} 6.689787
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 4.122522{col 49}{space 2} 1.265998{col 60}{space 1}    4.61{col 69}{space 3}0.000{col 77}{space 4} 2.258213{col 90}{space 3} 7.525947
{txt}{space 33}5  {c |}{col 37}{res}{space 2}  1.56396{col 49}{space 2}  .402279{col 60}{space 1}    1.74{col 69}{space 3}0.082{col 77}{space 4} .9446718{col 90}{space 3} 2.589227
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 3.572782{col 49}{space 2} .9116454{col 60}{space 1}    4.99{col 69}{space 3}0.000{col 77}{space 4} 2.166758{col 90}{space 3} 5.891183
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 6.283581{col 49}{space 2} 1.898727{col 60}{space 1}    6.08{col 69}{space 3}0.000{col 77}{space 4}  3.47534{col 90}{space 3} 11.36102
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 10.28028{col 49}{space 2} 3.925957{col 60}{space 1}    6.10{col 69}{space 3}0.000{col 77}{space 4} 4.863379{col 90}{space 3} 21.73062
{txt}{space 35} {c |}
{space 27}sbagency {c |}
{space 33}2  {c |}{col 37}{res}{space 2}  2.50618{col 49}{space 2} .6157447{col 60}{space 1}    3.74{col 69}{space 3}0.000{col 77}{space 4} 1.548389{col 90}{space 3} 4.056434
{txt}{space 33}3  {c |}{col 37}{res}{space 2} 1.660198{col 49}{space 2}  .384198{col 60}{space 1}    2.19{col 69}{space 3}0.028{col 77}{space 4} 1.054818{col 90}{space 3} 2.613018
{txt}{space 33}4  {c |}{col 37}{res}{space 2} 1.296526{col 49}{space 2} .2699308{col 60}{space 1}    1.25{col 69}{space 3}0.212{col 77}{space 4} .8621142{col 90}{space 3} 1.949833
{txt}{space 33}5  {c |}{col 37}{res}{space 2} 1.110763{col 49}{space 2}  .265033{col 60}{space 1}    0.44{col 69}{space 3}0.660{col 77}{space 4} .6958587{col 90}{space 3} 1.773054
{txt}{space 33}6  {c |}{col 37}{res}{space 2} 2.419852{col 49}{space 2} .5394981{col 60}{space 1}    3.96{col 69}{space 3}0.000{col 77}{space 4} 1.563206{col 90}{space 3} 3.745945
{txt}{space 33}7  {c |}{col 37}{res}{space 2} 1.777015{col 49}{space 2} .4580008{col 60}{space 1}    2.23{col 69}{space 3}0.026{col 77}{space 4} 1.072274{col 90}{space 3}  2.94494
{txt}{space 33}8  {c |}{col 37}{res}{space 2} 2.183623{col 49}{space 2} .5208302{col 60}{space 1}    3.27{col 69}{space 3}0.001{col 77}{space 4} 1.368207{col 90}{space 3} 3.485004
{txt}{space 33}9  {c |}{col 37}{res}{space 2} 1.939213{col 49}{space 2} .4439814{col 60}{space 1}    2.89{col 69}{space 3}0.004{col 77}{space 4} 1.238065{col 90}{space 3} 3.037438
{txt}{space 32}11  {c |}{col 37}{res}{space 2} 2.937358{col 49}{space 2} .9130342{col 60}{space 1}    3.47{col 69}{space 3}0.001{col 77}{space 4} 1.597253{col 90}{space 3} 5.401822
{txt}{space 32}12  {c |}{col 37}{res}{space 2} 1.771503{col 49}{space 2} .3051202{col 60}{space 1}    3.32{col 69}{space 3}0.001{col 77}{space 4} 1.263958{col 90}{space 3} 2.482854
{txt}{space 32}13  {c |}{col 37}{res}{space 2} 1.355742{col 49}{space 2} .2829598{col 60}{space 1}    1.46{col 69}{space 3}0.145{col 77}{space 4}  .900577{col 90}{space 3} 2.040953
{txt}{space 32}14  {c |}{col 37}{res}{space 2} 2.145443{col 49}{space 2} .5305522{col 60}{space 1}    3.09{col 69}{space 3}0.002{col 77}{space 4}  1.32136{col 90}{space 3} 3.483476
{txt}{space 32}15  {c |}{col 37}{res}{space 2} 1.469696{col 49}{space 2} .3378066{col 60}{space 1}    1.68{col 69}{space 3}0.094{col 77}{space 4} .9366567{col 90}{space 3}  2.30608
{txt}{space 32}16  {c |}{col 37}{res}{space 2} .8312415{col 49}{space 2} .1390902{col 60}{space 1}   -1.10{col 69}{space 3}0.269{col 77}{space 4} .5988212{col 90}{space 3} 1.153871
{txt}{space 32}17  {c |}{col 37}{res}{space 2} 1.623862{col 49}{space 2}  .138887{col 60}{space 1}    5.67{col 69}{space 3}0.000{col 77}{space 4} 1.373241{col 90}{space 3} 1.920222
{txt}{space 32}18  {c |}{col 37}{res}{space 2}  1.80505{col 49}{space 2} .4610893{col 60}{space 1}    2.31{col 69}{space 3}0.021{col 77}{space 4} 1.094094{col 90}{space 3} 2.977992
{txt}{space 32}19  {c |}{col 37}{res}{space 2} .6927715{col 49}{space 2} .1023024{col 60}{space 1}   -2.49{col 69}{space 3}0.013{col 77}{space 4} .5186711{col 90}{space 3} .9253115
{txt}{space 32}20  {c |}{col 37}{res}{space 2} .3307648{col 49}{space 2} .0934184{col 60}{space 1}   -3.92{col 69}{space 3}0.000{col 77}{space 4} .1901574{col 90}{space 3} .5753412
{txt}{space 32}21  {c |}{col 37}{res}{space 2} .8790715{col 49}{space 2} .0922763{col 60}{space 1}   -1.23{col 69}{space 3}0.219{col 77}{space 4} .7156051{col 90}{space 3} 1.079879
{txt}{space 32}22  {c |}{col 37}{res}{space 2} .4766645{col 49}{space 2} .1534685{col 60}{space 1}   -2.30{col 69}{space 3}0.021{col 77}{space 4} .2536046{col 90}{space 3} .8959185
{txt}{space 32}23  {c |}{col 37}{res}{space 2} 1.180158{col 49}{space 2} .2794658{col 60}{space 1}    0.70{col 69}{space 3}0.484{col 77}{space 4} .7419464{col 90}{space 3} 1.877188
{txt}{space 32}24  {c |}{col 37}{res}{space 2} .2844343{col 49}{space 2} .1174671{col 60}{space 1}   -3.04{col 69}{space 3}0.002{col 77}{space 4} .1266044{col 90}{space 3} .6390212
{txt}{space 32}25  {c |}{col 37}{res}{space 2} 1.428639{col 49}{space 2} .2300409{col 60}{space 1}    2.22{col 69}{space 3}0.027{col 77}{space 4} 1.041985{col 90}{space 3} 1.958772
{txt}{space 32}26  {c |}{col 37}{res}{space 2} .8062489{col 49}{space 2} .1268514{col 60}{space 1}   -1.37{col 69}{space 3}0.171{col 77}{space 4} .5923045{col 90}{space 3} 1.097471
{txt}{space 32}27  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}28  {c |}{col 37}{res}{space 2} 1.410488{col 49}{space 2} .1319083{col 60}{space 1}    3.68{col 69}{space 3}0.000{col 77}{space 4} 1.174263{col 90}{space 3} 1.694234
{txt}{space 32}29  {c |}{col 37}{res}{space 2} 2.886662{col 49}{space 2} .8685078{col 60}{space 1}    3.52{col 69}{space 3}0.000{col 77}{space 4} 1.600647{col 90}{space 3} 5.205905
{txt}{space 32}30  {c |}{col 37}{res}{space 2} 1.271964{col 49}{space 2} .3449482{col 60}{space 1}    0.89{col 69}{space 3}0.375{col 77}{space 4} .7475404{col 90}{space 3} 2.164288
{txt}{space 32}50  {c |}{col 37}{res}{space 2} 1.627359{col 49}{space 2} .2735574{col 60}{space 1}    2.90{col 69}{space 3}0.004{col 77}{space 4}  1.17057{col 90}{space 3}   2.2624
{txt}{space 32}51  {c |}{col 37}{res}{space 2} 3.087867{col 49}{space 2} .7669842{col 60}{space 1}    4.54{col 69}{space 3}0.000{col 77}{space 4} 1.897718{col 90}{space 3} 5.024415
{txt}{space 32}52  {c |}{col 37}{res}{space 2}  1.61608{col 49}{space 2} .5307929{col 60}{space 1}    1.46{col 69}{space 3}0.144{col 77}{space 4} .8489659{col 90}{space 3} 3.076348
{txt}{space 32}53  {c |}{col 37}{res}{space 2} 1.464598{col 49}{space 2} .1612258{col 60}{space 1}    3.47{col 69}{space 3}0.001{col 77}{space 4} 1.180365{col 90}{space 3} 1.817273
{txt}{space 32}54  {c |}{col 37}{res}{space 2} 1.404117{col 49}{space 2} .2463178{col 60}{space 1}    1.93{col 69}{space 3}0.053{col 77}{space 4} .9955913{col 90}{space 3} 1.980276
{txt}{space 32}55  {c |}{col 37}{res}{space 2} 1.347896{col 49}{space 2} .4065973{col 60}{space 1}    0.99{col 69}{space 3}0.322{col 77}{space 4} .7462571{col 90}{space 3}  2.43458
{txt}{space 32}56  {c |}{col 37}{res}{space 2} 1.149645{col 49}{space 2} .3693404{col 60}{space 1}    0.43{col 69}{space 3}0.664{col 77}{space 4} .6124955{col 90}{space 3} 2.157868
{txt}{space 32}57  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 32}58  {c |}{col 37}{res}{space 2} .8208883{col 49}{space 2} .2410981{col 60}{space 1}   -0.67{col 69}{space 3}0.502{col 77}{space 4}  .461618{col 90}{space 3} 1.459773
{txt}{space 32}59  {c |}{col 37}{res}{space 2} .3725328{col 49}{space 2} .0825993{col 60}{space 1}   -4.45{col 69}{space 3}0.000{col 77}{space 4} .2412309{col 90}{space 3} .5753021
{txt}{space 32}60  {c |}{col 37}{res}{space 2} .8611658{col 49}{space 2} .1212902{col 60}{space 1}   -1.06{col 69}{space 3}0.289{col 77}{space 4} .6534314{col 90}{space 3} 1.134942
{txt}{space 32}61  {c |}{col 37}{res}{space 2}        1{col 49}{txt}  (omitted)
{space 35} {c |}
{space 29}reagan {c |}{col 37}{res}{space 2} .0769507{col 49}{space 2}  .075127{col 60}{space 1}   -2.63{col 69}{space 3}0.009{col 77}{space 4} .0113549{col 90}{space 3}  .521484
{txt}{space 29}bush41 {c |}{col 37}{res}{space 2}  .187832{col 49}{space 2} .1174266{col 60}{space 1}   -2.67{col 69}{space 3}0.007{col 77}{space 4} .0551602{col 90}{space 3} .6396076
{txt}{space 28}clinton {c |}{col 37}{res}{space 2}  .712918{col 49}{space 2} .3872327{col 60}{space 1}   -0.62{col 69}{space 3}0.533{col 77}{space 4} .2458646{col 90}{space 3} 2.067203
{txt}{space 29}bush43 {c |}{col 37}{res}{space 2} .2792325{col 49}{space 2} .2132593{col 60}{space 1}   -1.67{col 69}{space 3}0.095{col 77}{space 4} .0624992{col 90}{space 3} 1.247549
{txt}{space 30}_cons {c |}{col 37}{res}{space 2} .0004216{col 49}{space 2} .0022974{col 60}{space 1}   -1.43{col 69}{space 3}0.154{col 77}{space 4} 9.70e-09{col 90}{space 3} 18.32966
{txt}{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 30}/ln_p {c |}{col 37}{res}{space 2} .9769769{col 49}{space 2} .0307756{col 60}{space 1}   31.75{col 69}{space 3}0.000{col 77}{space 4} .9166579{col 90}{space 3} 1.037296
{txt}{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                                  p {c |}{col 37}{res}{space 2} 2.656414{col 49}{space 2} .0817526{col 77}{space 4} 2.500918{col 90}{space 3} 2.821577
{txt}                                1/p {c |}{col 37}{res}{space 2} .3764474{col 49}{space 2} .0115854{col 77}{space 4} .3544117{col 90}{space 3} .3998531
{txt}{hline 36}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic 

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-830.8551{col 39}-506.1528{col 50}    24{col 58} 1060.306{col 69} 1174.472
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.soubinaryagency2nom#c.zpecompmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.soubinaryagency2nom#c.zpecompmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.337373{col 26}{space 2}  .172964{col 37}{space 1}    2.25{col 46}{space 3}0.025{col 54}{space 4} 1.037924{col 67}{space 3} 1.723215
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB22zpecom = r(table)
{txt}
{com}. mat list modelB22zpecom
{res}
{txt}modelB22zpecom[9,1]
              (1)
     b {res} 1.3373729
{txt}    se {res} .17296398
{txt}     z {res} 2.2477734
{txt}pvalue {res} .02459064
{txt}    ll {res} 1.0379242
{txt}    ul {res} 1.7232147
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. ** Generate 'manual' interaction variable ** 
. generate zpecomppdiff = soubinaryagency2nom*zpecompmedian
{txt}
{com}. 
. ** Re-Estimate Model 3  with 'manual' interaction variable **
. streg   zloyalmedian soubinaryagency2nom zpecomppdiff  zpecompmedian  zmecompmedian   toplevel2   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i.okstartadyr i.sbagency reagan bush41 clinton bush43, distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-611.75071}  
Iteration 2:{space 3}log pseudolikelihood = {res:-507.48169}  
Iteration 3:{space 3}log pseudolikelihood = {res:-506.15596}  
Iteration 4:{space 3}log pseudolikelihood = {res: -506.1528}  
Iteration 5:{space 3}log pseudolikelihood = {res: -506.1528}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res} -506.1528             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} .9963408{col 40}{space 2} .0737671{col 51}{space 1}   -0.05{col 60}{space 3}0.961{col 68}{space 4} .8617606{col 81}{space 3} 1.151938
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.062304{col 40}{space 2} .1906042{col 51}{space 1}    0.34{col 60}{space 3}0.736{col 68}{space 4} .7473456{col 81}{space 3} 1.509996
{txt}{space 14}zpecomppdiff {c |}{col 28}{res}{space 2} 1.237288{col 40}{space 2} .1172029{col 51}{space 1}    2.25{col 60}{space 3}0.025{col 68}{space 4} 1.027638{col 81}{space 3} 1.489709
{txt}{space 13}zpecompmedian {c |}{col 28}{res}{space 2} .9031864{col 40}{space 2} .0856467{col 51}{space 1}   -1.07{col 60}{space 3}0.283{col 68}{space 4} .7499983{col 81}{space 3} 1.087663
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9906859{col 40}{space 2} .0635315{col 51}{space 1}   -0.15{col 60}{space 3}0.884{col 68}{space 4} .8736741{col 81}{space 3} 1.123369
{txt}{space 17}toplevel2 {c |}{col 28}{res}{space 2} .5369567{col 40}{space 2} .0564068{col 51}{space 1}   -5.92{col 60}{space 3}0.000{col 68}{space 4} .4370401{col 81}{space 3} .6597164
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .7657247{col 40}{space 2} .1781615{col 51}{space 1}   -1.15{col 60}{space 3}0.251{col 68}{space 4} .4853144{col 81}{space 3} 1.208154
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .7337904{col 40}{space 2} .1755976{col 51}{space 1}   -1.29{col 60}{space 3}0.196{col 68}{space 4} .4590687{col 81}{space 3} 1.172914
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.487826{col 40}{space 2} .2519738{col 51}{space 1}    2.35{col 60}{space 3}0.019{col 68}{space 4} 1.067567{col 81}{space 3} 2.073524
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.623201{col 40}{space 2} .4180759{col 51}{space 1}    1.88{col 60}{space 3}0.060{col 68}{space 4} .9797932{col 81}{space 3} 2.689119
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 9.01e-11{col 40}{space 2} 9.47e-10{col 51}{space 1}   -2.20{col 60}{space 3}0.028{col 68}{space 4} 1.00e-19{col 81}{space 3} .0810311
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 559.9089{col 40}{space 2} 1297.626{col 51}{space 1}    2.73{col 60}{space 3}0.006{col 68}{space 4} 5.962133{col 81}{space 3} 52581.52
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1797963{col 40}{space 2} .0392101{col 51}{space 1}   -7.87{col 60}{space 3}0.000{col 68}{space 4} .1172601{col 81}{space 3} .2756838
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9924446{col 40}{space 2} .0046382{col 51}{space 1}   -1.62{col 60}{space 3}0.105{col 68}{space 4} .9833954{col 81}{space 3} 1.001577
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.130397{col 40}{space 2} .1039524{col 51}{space 1}    1.33{col 60}{space 3}0.183{col 68}{space 4} .9439604{col 81}{space 3} 1.353656
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.677727{col 40}{space 2} .3732354{col 51}{space 1}    2.33{col 60}{space 3}0.020{col 68}{space 4} 1.084823{col 81}{space 3}  2.59468
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.379084{col 40}{space 2} .9467543{col 51}{space 1}    6.83{col 60}{space 3}0.000{col 68}{space 4} 2.866515{col 81}{space 3} 6.689787
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 4.122522{col 40}{space 2} 1.265998{col 51}{space 1}    4.61{col 60}{space 3}0.000{col 68}{space 4} 2.258213{col 81}{space 3} 7.525947
{txt}{space 24}5  {c |}{col 28}{res}{space 2}  1.56396{col 40}{space 2}  .402279{col 51}{space 1}    1.74{col 60}{space 3}0.082{col 68}{space 4} .9446718{col 81}{space 3} 2.589227
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.572782{col 40}{space 2} .9116454{col 51}{space 1}    4.99{col 60}{space 3}0.000{col 68}{space 4} 2.166758{col 81}{space 3} 5.891183
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.283581{col 40}{space 2} 1.898727{col 51}{space 1}    6.08{col 60}{space 3}0.000{col 68}{space 4}  3.47534{col 81}{space 3} 11.36102
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 10.28028{col 40}{space 2} 3.925957{col 51}{space 1}    6.10{col 60}{space 3}0.000{col 68}{space 4} 4.863379{col 81}{space 3} 21.73062
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2}  2.50618{col 40}{space 2} .6157447{col 51}{space 1}    3.74{col 60}{space 3}0.000{col 68}{space 4} 1.548389{col 81}{space 3} 4.056434
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.660198{col 40}{space 2}  .384198{col 51}{space 1}    2.19{col 60}{space 3}0.028{col 68}{space 4} 1.054818{col 81}{space 3} 2.613018
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.296526{col 40}{space 2} .2699308{col 51}{space 1}    1.25{col 60}{space 3}0.212{col 68}{space 4} .8621142{col 81}{space 3} 1.949833
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.110763{col 40}{space 2}  .265033{col 51}{space 1}    0.44{col 60}{space 3}0.660{col 68}{space 4} .6958587{col 81}{space 3} 1.773054
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 2.419852{col 40}{space 2} .5394981{col 51}{space 1}    3.96{col 60}{space 3}0.000{col 68}{space 4} 1.563206{col 81}{space 3} 3.745945
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.777015{col 40}{space 2} .4580008{col 51}{space 1}    2.23{col 60}{space 3}0.026{col 68}{space 4} 1.072274{col 81}{space 3}  2.94494
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.183623{col 40}{space 2} .5208302{col 51}{space 1}    3.27{col 60}{space 3}0.001{col 68}{space 4} 1.368207{col 81}{space 3} 3.485004
{txt}{space 24}9  {c |}{col 28}{res}{space 2} 1.939213{col 40}{space 2} .4439814{col 51}{space 1}    2.89{col 60}{space 3}0.004{col 68}{space 4} 1.238065{col 81}{space 3} 3.037438
{txt}{space 23}11  {c |}{col 28}{res}{space 2} 2.937358{col 40}{space 2} .9130342{col 51}{space 1}    3.47{col 60}{space 3}0.001{col 68}{space 4} 1.597253{col 81}{space 3} 5.401822
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 1.771503{col 40}{space 2} .3051202{col 51}{space 1}    3.32{col 60}{space 3}0.001{col 68}{space 4} 1.263958{col 81}{space 3} 2.482854
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.355742{col 40}{space 2} .2829598{col 51}{space 1}    1.46{col 60}{space 3}0.145{col 68}{space 4}  .900577{col 81}{space 3} 2.040953
{txt}{space 23}14  {c |}{col 28}{res}{space 2} 2.145443{col 40}{space 2} .5305522{col 51}{space 1}    3.09{col 60}{space 3}0.002{col 68}{space 4}  1.32136{col 81}{space 3} 3.483476
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.469696{col 40}{space 2} .3378066{col 51}{space 1}    1.68{col 60}{space 3}0.094{col 68}{space 4} .9366567{col 81}{space 3}  2.30608
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8312415{col 40}{space 2} .1390902{col 51}{space 1}   -1.10{col 60}{space 3}0.269{col 68}{space 4} .5988212{col 81}{space 3} 1.153871
{txt}{space 23}17  {c |}{col 28}{res}{space 2} 1.623862{col 40}{space 2}  .138887{col 51}{space 1}    5.67{col 60}{space 3}0.000{col 68}{space 4} 1.373241{col 81}{space 3} 1.920222
{txt}{space 23}18  {c |}{col 28}{res}{space 2}  1.80505{col 40}{space 2} .4610893{col 51}{space 1}    2.31{col 60}{space 3}0.021{col 68}{space 4} 1.094094{col 81}{space 3} 2.977992
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .6927715{col 40}{space 2} .1023024{col 51}{space 1}   -2.49{col 60}{space 3}0.013{col 68}{space 4} .5186711{col 81}{space 3} .9253115
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .3307648{col 40}{space 2} .0934184{col 51}{space 1}   -3.92{col 60}{space 3}0.000{col 68}{space 4} .1901574{col 81}{space 3} .5753412
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .8790715{col 40}{space 2} .0922763{col 51}{space 1}   -1.23{col 60}{space 3}0.219{col 68}{space 4} .7156051{col 81}{space 3} 1.079879
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .4766645{col 40}{space 2} .1534685{col 51}{space 1}   -2.30{col 60}{space 3}0.021{col 68}{space 4} .2536046{col 81}{space 3} .8959185
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.180158{col 40}{space 2} .2794658{col 51}{space 1}    0.70{col 60}{space 3}0.484{col 68}{space 4} .7419464{col 81}{space 3} 1.877188
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .2844343{col 40}{space 2} .1174671{col 51}{space 1}   -3.04{col 60}{space 3}0.002{col 68}{space 4} .1266044{col 81}{space 3} .6390212
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.428639{col 40}{space 2} .2300409{col 51}{space 1}    2.22{col 60}{space 3}0.027{col 68}{space 4} 1.041985{col 81}{space 3} 1.958772
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .8062489{col 40}{space 2} .1268514{col 51}{space 1}   -1.37{col 60}{space 3}0.171{col 68}{space 4} .5923045{col 81}{space 3} 1.097471
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.410488{col 40}{space 2} .1319083{col 51}{space 1}    3.68{col 60}{space 3}0.000{col 68}{space 4} 1.174263{col 81}{space 3} 1.694234
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 2.886662{col 40}{space 2} .8685078{col 51}{space 1}    3.52{col 60}{space 3}0.000{col 68}{space 4} 1.600647{col 81}{space 3} 5.205905
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.271964{col 40}{space 2} .3449482{col 51}{space 1}    0.89{col 60}{space 3}0.375{col 68}{space 4} .7475404{col 81}{space 3} 2.164288
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 1.627359{col 40}{space 2} .2735574{col 51}{space 1}    2.90{col 60}{space 3}0.004{col 68}{space 4}  1.17057{col 81}{space 3}   2.2624
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 3.087867{col 40}{space 2} .7669842{col 51}{space 1}    4.54{col 60}{space 3}0.000{col 68}{space 4} 1.897718{col 81}{space 3} 5.024415
{txt}{space 23}52  {c |}{col 28}{res}{space 2}  1.61608{col 40}{space 2} .5307929{col 51}{space 1}    1.46{col 60}{space 3}0.144{col 68}{space 4} .8489659{col 81}{space 3} 3.076348
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.464598{col 40}{space 2} .1612258{col 51}{space 1}    3.47{col 60}{space 3}0.001{col 68}{space 4} 1.180365{col 81}{space 3} 1.817273
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.404117{col 40}{space 2} .2463178{col 51}{space 1}    1.93{col 60}{space 3}0.053{col 68}{space 4} .9955913{col 81}{space 3} 1.980276
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.347896{col 40}{space 2} .4065973{col 51}{space 1}    0.99{col 60}{space 3}0.322{col 68}{space 4} .7462571{col 81}{space 3}  2.43458
{txt}{space 23}56  {c |}{col 28}{res}{space 2} 1.149645{col 40}{space 2} .3693404{col 51}{space 1}    0.43{col 60}{space 3}0.664{col 68}{space 4} .6124955{col 81}{space 3} 2.157868
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} .8208883{col 40}{space 2} .2410981{col 51}{space 1}   -0.67{col 60}{space 3}0.502{col 68}{space 4}  .461618{col 81}{space 3} 1.459773
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3725328{col 40}{space 2} .0825993{col 51}{space 1}   -4.45{col 60}{space 3}0.000{col 68}{space 4} .2412309{col 81}{space 3} .5753021
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .8611658{col 40}{space 2} .1212902{col 51}{space 1}   -1.06{col 60}{space 3}0.289{col 68}{space 4} .6534314{col 81}{space 3} 1.134942
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0769507{col 40}{space 2}  .075127{col 51}{space 1}   -2.63{col 60}{space 3}0.009{col 68}{space 4} .0113549{col 81}{space 3}  .521484
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2}  .187832{col 40}{space 2} .1174266{col 51}{space 1}   -2.67{col 60}{space 3}0.007{col 68}{space 4} .0551602{col 81}{space 3} .6396076
{txt}{space 19}clinton {c |}{col 28}{res}{space 2}  .712918{col 40}{space 2} .3872327{col 51}{space 1}   -0.62{col 60}{space 3}0.533{col 68}{space 4} .2458646{col 81}{space 3} 2.067203
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2792325{col 40}{space 2} .2132593{col 51}{space 1}   -1.67{col 60}{space 3}0.095{col 68}{space 4} .0624992{col 81}{space 3} 1.247549
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .0004216{col 40}{space 2} .0022974{col 51}{space 1}   -1.43{col 60}{space 3}0.154{col 68}{space 4} 9.70e-09{col 81}{space 3} 18.32966
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9769769{col 40}{space 2} .0307756{col 51}{space 1}   31.75{col 60}{space 3}0.000{col 68}{space 4} .9166579{col 81}{space 3} 1.037296
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.656414{col 40}{space 2} .0817526{col 68}{space 4} 2.500918{col 81}{space 3} 2.821577
{txt}                       1/p {c |}{col 28}{res}{space 2} .3764474{col 40}{space 2} .0115854{col 68}{space 4} .3544117{col 81}{space 3} .3998531
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimate store modelb22a
{txt}
{com}. 
. 
. margins, predict(median time) at(zpecomppdiff=(-0.3960373 0.9692858))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1034.726{col 26}{space 2} 20.55387{col 37}{space 1}   50.34{col 46}{space 3}0.000{col 54}{space 4} 994.4412{col 67}{space 3} 1075.011
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 927.4659{col 26}{space 2} 38.81471{col 37}{space 1}   23.89{col 46}{space 3}0.000{col 54}{space 4} 851.3904{col 67}{space 3} 1003.541
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(zpecomppdiff=(-0.3960373 0.9692858))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     5.14{col 38}{space 2}   0.0234
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-107.2601{col 26}{space 2} 47.33114{col 37}{space 5}-200.0275{col 51}{space 3}-14.49281
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix modelB22azpecom = r(table)
{txt}
{com}. mat list modelB22azpecom
{res}
{txt}modelB22azpecom[9,1]
             r2vs1.
               _at
     b {res} -107.26014
{txt}    se {res}   47.33114
{txt}     z {res} -2.2661643
{txt}pvalue {res}  .02344133
{txt}    ll {res} -200.02747
{txt}    ul {res}  -14.49281
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. 
. estimates restore modelb22a
{txt}(results {stata estimates replay modelb22a:modelb22a} are active now)

{com}. 
. margins, predict(median time) at(zpecomppdiff=(-0.6451644 1.711348))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1055.596{col 26}{space 2} 27.52644{col 37}{space 1}   38.35{col 46}{space 3}0.000{col 54}{space 4} 1001.645{col 67}{space 3} 1109.546
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 873.9095{col 26}{space 2} 59.02131{col 37}{space 1}   14.81{col 46}{space 3}0.000{col 54}{space 4} 758.2299{col 67}{space 3} 989.5891
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, predict(median time) at(zpecomppdiff=(-0.6451644 1.711348))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zpecomppdiff}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     5.33{col 38}{space 2}   0.0210
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-181.6861{col 26}{space 2} 78.70716{col 37}{space 5}-335.9493{col 51}{space 3}-27.42292
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix modelB22bzpecom = r(table)
{txt}
{com}. mat list modelB22bzpecom
{res}
{txt}modelB22bzpecom[9,1]
             r2vs1.
               _at
     b {res} -181.68611
{txt}    se {res}  78.707159
{txt}     z {res}  -2.308381
{txt}pvalue {res}  .02097795
{txt}    ll {res} -335.94931
{txt}    ul {res} -27.422916
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. **********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. **** ALTERNATIVE MECHANISM B3: DOES APPOINTEE LOYALTY TRANSLATE INTO SHORTER [LONGER] SERVICE FOR TOP LEVEL [SUBORDIDATE LEVEL] POLITICAL EXECUTIVES?  ***
. 
. 
. 
. 
. **** MODEL B3.1: APPOINTEE LOYALTY X TOPLEVEL2 -- COX MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. stcox   c.zloyalmedian##i.toplevel2  zpecompmedian  zmecompmedian  soubinaryagency2nom  presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43,  hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur

{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
Iteration 0:   log pseudolikelihood = {res}-4793.4442
{txt}Iteration 1:   log pseudolikelihood = {res}-4507.0464
{txt}Iteration 2:   log pseudolikelihood = {res} -4480.917
{txt}Iteration 3:   log pseudolikelihood = {res}-4480.5638
{txt}Iteration 4:   log pseudolikelihood = {res}-4480.5634
{txt}Refining estimates:
Iteration 0:   log pseudolikelihood = {res}-4480.5634

{txt}Cox regression -- Breslow method for ties

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
                                                {txt}Wald chi2({res}40{txt})    =  {res}  73274.24
{txt}Log pseudolikelihood =   {res}-4480.5634             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} .8929403{col 40}{space 2} .0633971{col 51}{space 1}   -1.59{col 60}{space 3}0.111{col 68}{space 4} .7769422{col 81}{space 3} 1.026257
{txt}{space 15}1.toplevel2 {c |}{col 28}{res}{space 2} .4666709{col 40}{space 2}  .062846{col 51}{space 1}   -5.66{col 60}{space 3}0.000{col 68}{space 4} .3584102{col 81}{space 3} .6076325
{txt}{space 26} {c |}
{space 2}toplevel2#c.zloyalmedian {c |}
{space 24}1  {c |}{col 28}{res}{space 2} 1.208903{col 40}{space 2} .1449955{col 51}{space 1}    1.58{col 60}{space 3}0.114{col 68}{space 4} .9556493{col 81}{space 3}  1.52927
{txt}{space 26} {c |}
{space 13}zpecompmedian {c |}{col 28}{res}{space 2}  1.02501{col 40}{space 2} .0802256{col 51}{space 1}    0.32{col 60}{space 3}0.752{col 68}{space 4} .8792372{col 81}{space 3} 1.194951
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9771414{col 40}{space 2} .0632733{col 51}{space 1}   -0.36{col 60}{space 3}0.721{col 68}{space 4} .8606749{col 81}{space 3} 1.109368
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.049386{col 40}{space 2} .1714159{col 51}{space 1}    0.30{col 60}{space 3}0.768{col 68}{space 4} .7618906{col 81}{space 3} 1.445367
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .5719348{col 40}{space 2} .1569551{col 51}{space 1}   -2.04{col 60}{space 3}0.042{col 68}{space 4} .3340048{col 81}{space 3} .9793554
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .5568498{col 40}{space 2} .1593923{col 51}{space 1}   -2.05{col 60}{space 3}0.041{col 68}{space 4} .3177538{col 81}{space 3} .9758552
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.605656{col 40}{space 2}  .304658{col 51}{space 1}    2.50{col 60}{space 3}0.013{col 68}{space 4} 1.106994{col 81}{space 3} 2.328949
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 2.177796{col 40}{space 2} .6369003{col 51}{space 1}    2.66{col 60}{space 3}0.008{col 68}{space 4}  1.22767{col 81}{space 3} 3.863248
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 4.57e-11{col 40}{space 2} 4.82e-10{col 51}{space 1}   -2.26{col 60}{space 3}0.024{col 68}{space 4} 4.85e-20{col 81}{space 3} .0430829
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 600.5124{col 40}{space 2} 1417.455{col 51}{space 1}    2.71{col 60}{space 3}0.007{col 68}{space 4} 5.879459{col 81}{space 3} 61334.74
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1678183{col 40}{space 2} .0376892{col 51}{space 1}   -7.95{col 60}{space 3}0.000{col 68}{space 4} .1080622{col 81}{space 3} .2606183
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9919768{col 40}{space 2}  .004546{col 51}{space 1}   -1.76{col 60}{space 3}0.079{col 68}{space 4} .9831067{col 81}{space 3} 1.000927
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.137561{col 40}{space 2} .1048152{col 51}{space 1}    1.40{col 60}{space 3}0.162{col 68}{space 4} .9496083{col 81}{space 3} 1.362713
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.661195{col 40}{space 2} .3731529{col 51}{space 1}    2.26{col 60}{space 3}0.024{col 68}{space 4} 1.069586{col 81}{space 3} 2.580033
{txt}{space 24}3  {c |}{col 28}{res}{space 2}  3.95039{col 40}{space 2} .9030866{col 51}{space 1}    6.01{col 60}{space 3}0.000{col 68}{space 4} 2.523768{col 81}{space 3} 6.183446
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 3.788947{col 40}{space 2} 1.280463{col 51}{space 1}    3.94{col 60}{space 3}0.000{col 68}{space 4} 1.953699{col 81}{space 3} 7.348173
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.673309{col 40}{space 2} .4081123{col 51}{space 1}    2.11{col 60}{space 3}0.035{col 68}{space 4} 1.037461{col 81}{space 3} 2.698859
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.877165{col 40}{space 2} .9752821{col 51}{space 1}    5.39{col 60}{space 3}0.000{col 68}{space 4} 2.368092{col 81}{space 3} 6.347898
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.146111{col 40}{space 2} 1.831484{col 51}{space 1}    6.09{col 60}{space 3}0.000{col 68}{space 4} 3.427286{col 81}{space 3} 11.02175
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 9.075679{col 40}{space 2} 3.620804{col 51}{space 1}    5.53{col 60}{space 3}0.000{col 68}{space 4} 4.152278{col 81}{space 3} 19.83681
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 3.275768{col 40}{space 2} .9219298{col 51}{space 1}    4.22{col 60}{space 3}0.000{col 68}{space 4} 1.886912{col 81}{space 3} 5.686888
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 2.153703{col 40}{space 2} .5015198{col 51}{space 1}    3.29{col 60}{space 3}0.001{col 68}{space 4} 1.364494{col 81}{space 3} 3.399381
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.599964{col 40}{space 2} .3494446{col 51}{space 1}    2.15{col 60}{space 3}0.031{col 68}{space 4}   1.0428{col 81}{space 3} 2.454818
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.458707{col 40}{space 2} .4233651{col 51}{space 1}    1.30{col 60}{space 3}0.193{col 68}{space 4}  .825888{col 81}{space 3}  2.57641
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.231624{col 40}{space 2} .7605861{col 51}{space 1}    4.98{col 60}{space 3}0.000{col 68}{space 4} 2.037438{col 81}{space 3} 5.125749
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 2.148916{col 40}{space 2} .6195543{col 51}{space 1}    2.65{col 60}{space 3}0.008{col 68}{space 4} 1.221263{col 81}{space 3} 3.781198
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.747595{col 40}{space 2} .7577205{col 51}{space 1}    3.67{col 60}{space 3}0.000{col 68}{space 4} 1.600338{col 81}{space 3} 4.717301
{txt}{space 24}9  {c |}{col 28}{res}{space 2} 2.455492{col 40}{space 2} .6466377{col 51}{space 1}    3.41{col 60}{space 3}0.001{col 68}{space 4} 1.465481{col 81}{space 3} 4.114308
{txt}{space 23}11  {c |}{col 28}{res}{space 2} 4.198155{col 40}{space 2} 1.357441{col 51}{space 1}    4.44{col 60}{space 3}0.000{col 68}{space 4} 2.227558{col 81}{space 3} 7.912029
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 2.400349{col 40}{space 2} .5512268{col 51}{space 1}    3.81{col 60}{space 3}0.000{col 68}{space 4} 1.530385{col 81}{space 3} 3.764853
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.809434{col 40}{space 2} .4265491{col 51}{space 1}    2.52{col 60}{space 3}0.012{col 68}{space 4} 1.139944{col 81}{space 3} 2.872115
{txt}{space 23}14  {c |}{col 28}{res}{space 2}  2.98754{col 40}{space 2} .8550656{col 51}{space 1}    3.82{col 60}{space 3}0.000{col 68}{space 4} 1.704869{col 81}{space 3} 5.235241
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.762415{col 40}{space 2}  .471098{col 51}{space 1}    2.12{col 60}{space 3}0.034{col 68}{space 4}  1.04371{col 81}{space 3} 2.976025
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8265285{col 40}{space 2} .1230996{col 51}{space 1}   -1.28{col 60}{space 3}0.201{col 68}{space 4}  .617282{col 81}{space 3} 1.106706
{txt}{space 23}17  {c |}{col 28}{res}{space 2} 1.603273{col 40}{space 2} .1342107{col 51}{space 1}    5.64{col 60}{space 3}0.000{col 68}{space 4} 1.360671{col 81}{space 3} 1.889131
{txt}{space 23}18  {c |}{col 28}{res}{space 2}  2.29133{col 40}{space 2} .6412616{col 51}{space 1}    2.96{col 60}{space 3}0.003{col 68}{space 4} 1.323935{col 81}{space 3} 3.965598
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .7080826{col 40}{space 2} .1045423{col 51}{space 1}   -2.34{col 60}{space 3}0.019{col 68}{space 4} .5301653{col 81}{space 3} .9457068
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .2432391{col 40}{space 2}  .078185{col 51}{space 1}   -4.40{col 60}{space 3}0.000{col 68}{space 4} .1295476{col 81}{space 3} .4567067
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .9037893{col 40}{space 2} .0747963{col 51}{space 1}   -1.22{col 60}{space 3}0.222{col 68}{space 4}  .768463{col 81}{space 3} 1.062947
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .4697775{col 40}{space 2} .1651446{col 51}{space 1}   -2.15{col 60}{space 3}0.032{col 68}{space 4} .2358646{col 81}{space 3}  .935668
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.008324{col 40}{space 2} .2455827{col 51}{space 1}    0.03{col 60}{space 3}0.973{col 68}{space 4} .6255833{col 81}{space 3} 1.625229
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .2098266{col 40}{space 2} .0964145{col 51}{space 1}   -3.40{col 60}{space 3}0.001{col 68}{space 4} .0852583{col 81}{space 3} .5163979
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.621259{col 40}{space 2} .2208662{col 51}{space 1}    3.55{col 60}{space 3}0.000{col 68}{space 4} 1.241343{col 81}{space 3} 2.117447
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .7381677{col 40}{space 2} .1113821{col 51}{space 1}   -2.01{col 60}{space 3}0.044{col 68}{space 4} .5491833{col 81}{space 3} .9921853
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.670708{col 40}{space 2} .1630214{col 51}{space 1}    5.26{col 60}{space 3}0.000{col 68}{space 4} 1.379887{col 81}{space 3} 2.022821
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 4.045787{col 40}{space 2} 1.378293{col 51}{space 1}    4.10{col 60}{space 3}0.000{col 68}{space 4} 2.075015{col 81}{space 3} 7.888327
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.535847{col 40}{space 2}  .441442{col 51}{space 1}    1.49{col 60}{space 3}0.135{col 68}{space 4}  .874361{col 81}{space 3} 2.697772
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 2.205713{col 40}{space 2} .4701018{col 51}{space 1}    3.71{col 60}{space 3}0.000{col 68}{space 4} 1.452557{col 81}{space 3} 3.349384
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 4.338558{col 40}{space 2} 1.120796{col 51}{space 1}    5.68{col 60}{space 3}0.000{col 68}{space 4} 2.614877{col 81}{space 3} 7.198459
{txt}{space 23}52  {c |}{col 28}{res}{space 2}  2.08933{col 40}{space 2} .7750957{col 51}{space 1}    1.99{col 60}{space 3}0.047{col 68}{space 4} 1.009787{col 81}{space 3}  4.32299
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.539387{col 40}{space 2} .1583748{col 51}{space 1}    4.19{col 60}{space 3}0.000{col 68}{space 4} 1.258273{col 81}{space 3} 1.883306
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.949672{col 40}{space 2}  .402149{col 51}{space 1}    3.24{col 60}{space 3}0.001{col 68}{space 4} 1.301333{col 81}{space 3} 2.921021
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 2.089157{col 40}{space 2} .7542639{col 51}{space 1}    2.04{col 60}{space 3}0.041{col 68}{space 4} 1.029569{col 81}{space 3} 4.239227
{txt}{space 23}56  {c |}{col 28}{res}{space 2}  1.55131{col 40}{space 2} .5279146{col 51}{space 1}    1.29{col 60}{space 3}0.197{col 68}{space 4} .7962189{col 81}{space 3} 3.022488
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} 1.183456{col 40}{space 2} .4510661{col 51}{space 1}    0.44{col 60}{space 3}0.659{col 68}{space 4} .5606896{col 81}{space 3} 2.497939
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3766872{col 40}{space 2} .1364528{col 51}{space 1}   -2.70{col 60}{space 3}0.007{col 68}{space 4} .1851987{col 81}{space 3} .7661676
{txt}{space 23}60  {c |}{col 28}{res}{space 2} 1.033325{col 40}{space 2} .1370068{col 51}{space 1}    0.25{col 60}{space 3}0.805{col 68}{space 4} .7968517{col 81}{space 3} 1.339974
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0701118{col 40}{space 2} .0692684{col 51}{space 1}   -2.69{col 60}{space 3}0.007{col 68}{space 4} .0101118{col 81}{space 3} .4861307
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1855399{col 40}{space 2} .1183039{col 51}{space 1}   -2.64{col 60}{space 3}0.008{col 68}{space 4} .0531734{col 81}{space 3} .6474111
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6923792{col 40}{space 2} .3702465{col 51}{space 1}   -0.69{col 60}{space 3}0.492{col 68}{space 4} .2427549{col 81}{space 3} 1.974786
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2721192{col 40}{space 2} .2087599{col 51}{space 1}   -1.70{col 60}{space 3}0.090{col 68}{space 4}  .060499{col 81}{space 3} 1.223968
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-4793.444{col 39}-4480.563{col 50}    40{col 58} 9041.127{col 69} 9231.404
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}TOP LEVEL − SUBORDINATE Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.toplevel2#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.toplevel2#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  1.29566{col 26}{space 2} .2121726{col 37}{space 1}    1.58{col 46}{space 3}0.114{col 54}{space 4} .9399423{col 67}{space 3} 1.785997
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB31zloyal = r(table)
{txt}
{com}. mat list modelB31zloyal
{res}
{txt}modelB31zloyal[9,1]
              (1)
     b {res} 1.2956596
{txt}    se {res} .21217264
{txt}     z {res} 1.5817387
{txt}pvalue {res} .11370924
{txt}    ll {res} .93994226
{txt}    ul {res} 1.7859968
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. **** MODEL B3.2: APPOINTEE LOYALTY X TOPLEVEL2 -- WEIBULL MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. streg   c.zloyalmedian##i.toplevel2  zpecompmedian  zmecompmedian  soubinaryagency2nom   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-608.30612}  
Iteration 2:{space 3}log pseudolikelihood = {res:-508.67493}  
Iteration 3:{space 3}log pseudolikelihood = {res:-507.43811}  
Iteration 4:{space 3}log pseudolikelihood = {res:-507.43566}  
Iteration 5:{space 3}log pseudolikelihood = {res:-507.43566}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-507.43566             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} .9047037{col 40}{space 2} .0626131{col 51}{space 1}   -1.45{col 60}{space 3}0.148{col 68}{space 4} .7899436{col 81}{space 3} 1.036136
{txt}{space 15}1.toplevel2 {c |}{col 28}{res}{space 2}   .49491{col 40}{space 2}  .066535{col 51}{space 1}   -5.23{col 60}{space 3}0.000{col 68}{space 4} .3802698{col 81}{space 3} .6441108
{txt}{space 26} {c |}
{space 2}toplevel2#c.zloyalmedian {c |}
{space 24}1  {c |}{col 28}{res}{space 2} 1.186742{col 40}{space 2} .1469306{col 51}{space 1}    1.38{col 60}{space 3}0.167{col 68}{space 4} .9310417{col 81}{space 3} 1.512668
{txt}{space 26} {c |}
{space 13}zpecompmedian {c |}{col 28}{res}{space 2} 1.036603{col 40}{space 2} .0803547{col 51}{space 1}    0.46{col 60}{space 3}0.643{col 68}{space 4} .8904916{col 81}{space 3} 1.206689
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9798048{col 40}{space 2} .0622982{col 51}{space 1}   -0.32{col 60}{space 3}0.748{col 68}{space 4} .8650043{col 81}{space 3} 1.109841
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.052938{col 40}{space 2} .1765472{col 51}{space 1}    0.31{col 60}{space 3}0.758{col 68}{space 4} .7580201{col 81}{space 3} 1.462597
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .6475439{col 40}{space 2} .1710804{col 51}{space 1}   -1.64{col 60}{space 3}0.100{col 68}{space 4} .3858182{col 81}{space 3} 1.086815
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .6233029{col 40}{space 2} .1711577{col 51}{space 1}   -1.72{col 60}{space 3}0.085{col 68}{space 4} .3638823{col 81}{space 3} 1.067671
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.537442{col 40}{space 2} .2836352{col 51}{space 1}    2.33{col 60}{space 3}0.020{col 68}{space 4} 1.070939{col 81}{space 3} 2.207155
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.850279{col 40}{space 2}  .517588{col 51}{space 1}    2.20{col 60}{space 3}0.028{col 68}{space 4} 1.069366{col 81}{space 3} 3.201461
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 2.35e-10{col 40}{space 2} 2.47e-09{col 51}{space 1}   -2.10{col 60}{space 3}0.035{col 68}{space 4} 2.51e-19{col 81}{space 3} .2188085
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 459.1028{col 40}{space 2} 1081.915{col 51}{space 1}    2.60{col 60}{space 3}0.009{col 68}{space 4} 4.528772{col 81}{space 3} 46541.41
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1776922{col 40}{space 2} .0391926{col 51}{space 1}   -7.83{col 60}{space 3}0.000{col 68}{space 4} .1153251{col 81}{space 3} .2737872
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9925836{col 40}{space 2}  .004614{col 51}{space 1}   -1.60{col 60}{space 3}0.109{col 68}{space 4} .9835814{col 81}{space 3} 1.001668
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.126058{col 40}{space 2} .1045731{col 51}{space 1}    1.28{col 60}{space 3}0.201{col 68}{space 4} .9386691{col 81}{space 3} 1.350855
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.690098{col 40}{space 2} .3745408{col 51}{space 1}    2.37{col 60}{space 3}0.018{col 68}{space 4} 1.094657{col 81}{space 3}  2.60943
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.398439{col 40}{space 2} .9624367{col 51}{space 1}    6.77{col 60}{space 3}0.000{col 68}{space 4} 2.864471{col 81}{space 3}  6.75387
{txt}{space 24}4  {c |}{col 28}{res}{space 2}  4.20126{col 40}{space 2} 1.337581{col 51}{space 1}    4.51{col 60}{space 3}0.000{col 68}{space 4} 2.251009{col 81}{space 3} 7.841188
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.558716{col 40}{space 2}  .390412{col 51}{space 1}    1.77{col 60}{space 3}0.076{col 68}{space 4} .9540393{col 81}{space 3} 2.546641
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.606465{col 40}{space 2} .9114441{col 51}{space 1}    5.08{col 60}{space 3}0.000{col 68}{space 4} 2.197666{col 81}{space 3} 5.918364
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.775836{col 40}{space 2} 1.961892{col 51}{space 1}    6.61{col 60}{space 3}0.000{col 68}{space 4} 3.841527{col 81}{space 3} 11.95149
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 10.04076{col 40}{space 2} 3.976505{col 51}{space 1}    5.82{col 60}{space 3}0.000{col 68}{space 4} 4.620194{col 81}{space 3} 21.82093
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 2.852882{col 40}{space 2} .7574179{col 51}{space 1}    3.95{col 60}{space 3}0.000{col 68}{space 4} 1.695494{col 81}{space 3} 4.800331
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.888598{col 40}{space 2} .4208475{col 51}{space 1}    2.85{col 60}{space 3}0.004{col 68}{space 4} 1.220285{col 81}{space 3} 2.922926
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.471776{col 40}{space 2} .2910833{col 51}{space 1}    1.95{col 60}{space 3}0.051{col 68}{space 4} .9988353{col 81}{space 3} 2.168652
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.322463{col 40}{space 2} .3775349{col 51}{space 1}    0.98{col 60}{space 3}0.328{col 68}{space 4}   .75576{col 81}{space 3} 2.314107
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 2.819571{col 40}{space 2} .6498372{col 51}{space 1}    4.50{col 60}{space 3}0.000{col 68}{space 4} 1.794748{col 81}{space 3} 4.429582
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.938689{col 40}{space 2} .5356933{col 51}{space 1}    2.40{col 60}{space 3}0.017{col 68}{space 4} 1.127993{col 81}{space 3} 3.332038
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.451102{col 40}{space 2} .6333132{col 51}{space 1}    3.47{col 60}{space 3}0.001{col 68}{space 4} 1.477164{col 81}{space 3} 4.067185
{txt}{space 24}9  {c |}{col 28}{res}{space 2}   2.2203{col 40}{space 2} .5502981{col 51}{space 1}    3.22{col 60}{space 3}0.001{col 68}{space 4} 1.365975{col 81}{space 3} 3.608949
{txt}{space 23}11  {c |}{col 28}{res}{space 2} 3.562357{col 40}{space 2} 1.119577{col 51}{space 1}    4.04{col 60}{space 3}0.000{col 68}{space 4} 1.924075{col 81}{space 3} 6.595578
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 2.197713{col 40}{space 2} .4793314{col 51}{space 1}    3.61{col 60}{space 3}0.000{col 68}{space 4} 1.433244{col 81}{space 3} 3.369939
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.604059{col 40}{space 2} .3566402{col 51}{space 1}    2.13{col 60}{space 3}0.034{col 68}{space 4} 1.037451{col 81}{space 3} 2.480123
{txt}{space 23}14  {c |}{col 28}{res}{space 2} 2.530402{col 40}{space 2} .6938881{col 51}{space 1}    3.39{col 60}{space 3}0.001{col 68}{space 4} 1.478334{col 81}{space 3} 4.331182
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.617514{col 40}{space 2} .4089849{col 51}{space 1}    1.90{col 60}{space 3}0.057{col 68}{space 4} .9854247{col 81}{space 3} 2.655048
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8155819{col 40}{space 2} .1298776{col 51}{space 1}   -1.28{col 60}{space 3}0.201{col 68}{space 4} .5969221{col 81}{space 3} 1.114339
{txt}{space 23}17  {c |}{col 28}{res}{space 2}   1.6027{col 40}{space 2} .1367883{col 51}{space 1}    5.53{col 60}{space 3}0.000{col 68}{space 4} 1.355824{col 81}{space 3} 1.894528
{txt}{space 23}18  {c |}{col 28}{res}{space 2} 2.028617{col 40}{space 2} .5304481{col 51}{space 1}    2.71{col 60}{space 3}0.007{col 68}{space 4} 1.215138{col 81}{space 3} 3.386682
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .7116872{col 40}{space 2} .1027976{col 51}{space 1}   -2.35{col 60}{space 3}0.019{col 68}{space 4}  .536216{col 81}{space 3} .9445795
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .2909665{col 40}{space 2} .0870607{col 51}{space 1}   -4.13{col 60}{space 3}0.000{col 68}{space 4} .1618651{col 81}{space 3} .5230375
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .9425171{col 40}{space 2} .0852772{col 51}{space 1}   -0.65{col 60}{space 3}0.513{col 68}{space 4} .7893582{col 81}{space 3} 1.125393
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .5184054{col 40}{space 2} .1709007{col 51}{space 1}   -1.99{col 60}{space 3}0.046{col 68}{space 4} .2716797{col 81}{space 3} .9891947
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.160041{col 40}{space 2} .2861413{col 51}{space 1}    0.60{col 60}{space 3}0.547{col 68}{space 4} .7153389{col 81}{space 3} 1.881199
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .2369469{col 40}{space 2} .0873265{col 51}{space 1}   -3.91{col 60}{space 3}0.000{col 68}{space 4} .1150646{col 81}{space 3} .4879332
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.706087{col 40}{space 2} .2527316{col 51}{space 1}    3.61{col 60}{space 3}0.000{col 68}{space 4} 1.276169{col 81}{space 3} 2.280836
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .7465826{col 40}{space 2} .1255913{col 51}{space 1}   -1.74{col 60}{space 3}0.082{col 68}{space 4} .5368925{col 81}{space 3}  1.03817
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.488302{col 40}{space 2} .1468903{col 51}{space 1}    4.03{col 60}{space 3}0.000{col 68}{space 4} 1.226536{col 81}{space 3} 1.805933
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 3.436257{col 40}{space 2} 1.078795{col 51}{space 1}    3.93{col 60}{space 3}0.000{col 68}{space 4} 1.857186{col 81}{space 3} 6.357933
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.367134{col 40}{space 2} .3912907{col 51}{space 1}    1.09{col 60}{space 3}0.275{col 68}{space 4} .7801651{col 81}{space 3} 2.395717
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 1.984802{col 40}{space 2} .4218842{col 51}{space 1}    3.23{col 60}{space 3}0.001{col 68}{space 4} 1.308543{col 81}{space 3} 3.010553
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 3.776343{col 40}{space 2} .9089389{col 51}{space 1}    5.52{col 60}{space 3}0.000{col 68}{space 4} 2.356098{col 81}{space 3} 6.052706
{txt}{space 23}52  {c |}{col 28}{res}{space 2} 2.078133{col 40}{space 2} .7636265{col 51}{space 1}    1.99{col 60}{space 3}0.047{col 68}{space 4} 1.011329{col 81}{space 3} 4.270258
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.512308{col 40}{space 2} .1663887{col 51}{space 1}    3.76{col 60}{space 3}0.000{col 68}{space 4} 1.218957{col 81}{space 3} 1.876255
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.737185{col 40}{space 2}  .351844{col 51}{space 1}    2.73{col 60}{space 3}0.006{col 68}{space 4}  1.16801{col 81}{space 3} 2.583722
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.712431{col 40}{space 2} .5844244{col 51}{space 1}    1.58{col 60}{space 3}0.115{col 68}{space 4}  .877227{col 81}{space 3} 3.342829
{txt}{space 23}56  {c |}{col 28}{res}{space 2}  1.45735{col 40}{space 2} .4884353{col 51}{space 1}    1.12{col 60}{space 3}0.261{col 68}{space 4} .7555809{col 81}{space 3} 2.810908
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} .9529134{col 40}{space 2}  .382963{col 51}{space 1}   -0.12{col 60}{space 3}0.904{col 68}{space 4}  .433478{col 81}{space 3} 2.094787
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3926094{col 40}{space 2} .1012673{col 51}{space 1}   -3.62{col 60}{space 3}0.000{col 68}{space 4} .2368137{col 81}{space 3} .6509004
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .8803898{col 40}{space 2} .1157186{col 51}{space 1}   -0.97{col 60}{space 3}0.332{col 68}{space 4} .6804448{col 81}{space 3} 1.139087
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0791498{col 40}{space 2}  .078035{col 51}{space 1}   -2.57{col 60}{space 3}0.010{col 68}{space 4} .0114614{col 81}{space 3} .5465913
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1905178{col 40}{space 2} .1211122{col 51}{space 1}   -2.61{col 60}{space 3}0.009{col 68}{space 4} .0548058{col 81}{space 3} .6622846
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6645376{col 40}{space 2} .3606237{col 51}{space 1}   -0.75{col 60}{space 3}0.451{col 68}{space 4}  .229403{col 81}{space 3} 1.925041
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2755563{col 40}{space 2} .2109404{col 51}{space 1}   -1.68{col 60}{space 3}0.092{col 68}{space 4} .0614624{col 81}{space 3} 1.235411
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .0002835{col 40}{space 2} .0015558{col 51}{space 1}   -1.49{col 60}{space 3}0.137{col 68}{space 4} 6.04e-09{col 81}{space 3} 13.31214
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9775781{col 40}{space 2} .0310865{col 51}{space 1}   31.45{col 60}{space 3}0.000{col 68}{space 4} .9166498{col 81}{space 3} 1.038506
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.658011{col 40}{space 2} .0826282{col 68}{space 4} 2.500898{col 81}{space 3} 2.824995
{txt}                       1/p {c |}{col 28}{res}{space 2} .3762212{col 40}{space 2} .0116954{col 68}{space 4}  .353983{col 81}{space 3} .3998564
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-830.8551{col 39}-507.4357{col 50}    24{col 58} 1062.871{col 69} 1177.038
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}TOP LEVEL − SUBORDINATE Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest 1.toplevel2#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}1.toplevel2#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.263341{col 26}{space 2}  .213556{col 37}{space 1}    1.38{col 46}{space 3}0.167{col 54}{space 4} .9070533{col 67}{space 3} 1.759577
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB32zloyal = r(table)
{txt}
{com}. mat list modelB32zloyal
{res}
{txt}modelB32zloyal[9,1]
              (1)
     b {res} 1.2633408
{txt}    se {res}   .213556
{txt}     z {res}   1.38286
{txt}pvalue {res}  .1667078
{txt}    ll {res}  .9070533
{txt}    ul {res} 1.7595767
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. ** Generate 'manual' interaction variable ** 
. generate zloytopppdiff = toplevel2*zloyalmedian
{txt}
{com}. 
. ** Re-Estimate Model 3  with 'manual' interaction variable **
. streg   zloyalmedian toplevel2 zloytopppdiff  zpecompmedian  zmecompmedian  soubinaryagency2nom   presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp  okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-608.30612}  
Iteration 2:{space 3}log pseudolikelihood = {res:-508.67493}  
Iteration 3:{space 3}log pseudolikelihood = {res:-507.43811}  
Iteration 4:{space 3}log pseudolikelihood = {res:-507.43566}  
Iteration 5:{space 3}log pseudolikelihood = {res:-507.43566}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-507.43566             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} .9047037{col 40}{space 2} .0626131{col 51}{space 1}   -1.45{col 60}{space 3}0.148{col 68}{space 4} .7899436{col 81}{space 3} 1.036136
{txt}{space 17}toplevel2 {c |}{col 28}{res}{space 2}   .49491{col 40}{space 2}  .066535{col 51}{space 1}   -5.23{col 60}{space 3}0.000{col 68}{space 4} .3802698{col 81}{space 3} .6441108
{txt}{space 13}zloytopppdiff {c |}{col 28}{res}{space 2} 1.186742{col 40}{space 2} .1469306{col 51}{space 1}    1.38{col 60}{space 3}0.167{col 68}{space 4} .9310417{col 81}{space 3} 1.512668
{txt}{space 13}zpecompmedian {c |}{col 28}{res}{space 2} 1.036603{col 40}{space 2} .0803547{col 51}{space 1}    0.46{col 60}{space 3}0.643{col 68}{space 4} .8904916{col 81}{space 3} 1.206689
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9798048{col 40}{space 2} .0622982{col 51}{space 1}   -0.32{col 60}{space 3}0.748{col 68}{space 4} .8650043{col 81}{space 3} 1.109841
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.052938{col 40}{space 2} .1765472{col 51}{space 1}    0.31{col 60}{space 3}0.758{col 68}{space 4} .7580201{col 81}{space 3} 1.462597
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .6475439{col 40}{space 2} .1710804{col 51}{space 1}   -1.64{col 60}{space 3}0.100{col 68}{space 4} .3858182{col 81}{space 3} 1.086815
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .6233029{col 40}{space 2} .1711577{col 51}{space 1}   -1.72{col 60}{space 3}0.085{col 68}{space 4} .3638823{col 81}{space 3} 1.067671
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.537442{col 40}{space 2} .2836352{col 51}{space 1}    2.33{col 60}{space 3}0.020{col 68}{space 4} 1.070939{col 81}{space 3} 2.207155
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.850279{col 40}{space 2}  .517588{col 51}{space 1}    2.20{col 60}{space 3}0.028{col 68}{space 4} 1.069366{col 81}{space 3} 3.201461
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 2.35e-10{col 40}{space 2} 2.47e-09{col 51}{space 1}   -2.10{col 60}{space 3}0.035{col 68}{space 4} 2.51e-19{col 81}{space 3} .2188085
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 459.1028{col 40}{space 2} 1081.915{col 51}{space 1}    2.60{col 60}{space 3}0.009{col 68}{space 4} 4.528772{col 81}{space 3} 46541.41
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1776922{col 40}{space 2} .0391926{col 51}{space 1}   -7.83{col 60}{space 3}0.000{col 68}{space 4} .1153251{col 81}{space 3} .2737872
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9925836{col 40}{space 2}  .004614{col 51}{space 1}   -1.60{col 60}{space 3}0.109{col 68}{space 4} .9835814{col 81}{space 3} 1.001668
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.126058{col 40}{space 2} .1045731{col 51}{space 1}    1.28{col 60}{space 3}0.201{col 68}{space 4} .9386691{col 81}{space 3} 1.350855
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.690098{col 40}{space 2} .3745408{col 51}{space 1}    2.37{col 60}{space 3}0.018{col 68}{space 4} 1.094657{col 81}{space 3}  2.60943
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.398439{col 40}{space 2} .9624367{col 51}{space 1}    6.77{col 60}{space 3}0.000{col 68}{space 4} 2.864471{col 81}{space 3}  6.75387
{txt}{space 24}4  {c |}{col 28}{res}{space 2}  4.20126{col 40}{space 2} 1.337581{col 51}{space 1}    4.51{col 60}{space 3}0.000{col 68}{space 4} 2.251009{col 81}{space 3} 7.841188
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.558716{col 40}{space 2}  .390412{col 51}{space 1}    1.77{col 60}{space 3}0.076{col 68}{space 4} .9540393{col 81}{space 3} 2.546641
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.606465{col 40}{space 2} .9114441{col 51}{space 1}    5.08{col 60}{space 3}0.000{col 68}{space 4} 2.197666{col 81}{space 3} 5.918364
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.775836{col 40}{space 2} 1.961892{col 51}{space 1}    6.61{col 60}{space 3}0.000{col 68}{space 4} 3.841527{col 81}{space 3} 11.95149
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 10.04076{col 40}{space 2} 3.976505{col 51}{space 1}    5.82{col 60}{space 3}0.000{col 68}{space 4} 4.620194{col 81}{space 3} 21.82093
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 2.852882{col 40}{space 2} .7574179{col 51}{space 1}    3.95{col 60}{space 3}0.000{col 68}{space 4} 1.695494{col 81}{space 3} 4.800331
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.888598{col 40}{space 2} .4208475{col 51}{space 1}    2.85{col 60}{space 3}0.004{col 68}{space 4} 1.220285{col 81}{space 3} 2.922926
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.471776{col 40}{space 2} .2910833{col 51}{space 1}    1.95{col 60}{space 3}0.051{col 68}{space 4} .9988353{col 81}{space 3} 2.168652
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.322463{col 40}{space 2} .3775349{col 51}{space 1}    0.98{col 60}{space 3}0.328{col 68}{space 4}   .75576{col 81}{space 3} 2.314107
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 2.819571{col 40}{space 2} .6498372{col 51}{space 1}    4.50{col 60}{space 3}0.000{col 68}{space 4} 1.794748{col 81}{space 3} 4.429582
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.938689{col 40}{space 2} .5356933{col 51}{space 1}    2.40{col 60}{space 3}0.017{col 68}{space 4} 1.127993{col 81}{space 3} 3.332038
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.451102{col 40}{space 2} .6333132{col 51}{space 1}    3.47{col 60}{space 3}0.001{col 68}{space 4} 1.477164{col 81}{space 3} 4.067185
{txt}{space 24}9  {c |}{col 28}{res}{space 2}   2.2203{col 40}{space 2} .5502981{col 51}{space 1}    3.22{col 60}{space 3}0.001{col 68}{space 4} 1.365975{col 81}{space 3} 3.608949
{txt}{space 23}11  {c |}{col 28}{res}{space 2} 3.562357{col 40}{space 2} 1.119577{col 51}{space 1}    4.04{col 60}{space 3}0.000{col 68}{space 4} 1.924075{col 81}{space 3} 6.595578
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 2.197713{col 40}{space 2} .4793314{col 51}{space 1}    3.61{col 60}{space 3}0.000{col 68}{space 4} 1.433244{col 81}{space 3} 3.369939
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.604059{col 40}{space 2} .3566402{col 51}{space 1}    2.13{col 60}{space 3}0.034{col 68}{space 4} 1.037451{col 81}{space 3} 2.480123
{txt}{space 23}14  {c |}{col 28}{res}{space 2} 2.530402{col 40}{space 2} .6938881{col 51}{space 1}    3.39{col 60}{space 3}0.001{col 68}{space 4} 1.478334{col 81}{space 3} 4.331182
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.617514{col 40}{space 2} .4089849{col 51}{space 1}    1.90{col 60}{space 3}0.057{col 68}{space 4} .9854247{col 81}{space 3} 2.655048
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8155819{col 40}{space 2} .1298776{col 51}{space 1}   -1.28{col 60}{space 3}0.201{col 68}{space 4} .5969221{col 81}{space 3} 1.114339
{txt}{space 23}17  {c |}{col 28}{res}{space 2}   1.6027{col 40}{space 2} .1367883{col 51}{space 1}    5.53{col 60}{space 3}0.000{col 68}{space 4} 1.355824{col 81}{space 3} 1.894528
{txt}{space 23}18  {c |}{col 28}{res}{space 2} 2.028617{col 40}{space 2} .5304481{col 51}{space 1}    2.71{col 60}{space 3}0.007{col 68}{space 4} 1.215138{col 81}{space 3} 3.386682
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .7116872{col 40}{space 2} .1027976{col 51}{space 1}   -2.35{col 60}{space 3}0.019{col 68}{space 4}  .536216{col 81}{space 3} .9445795
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .2909665{col 40}{space 2} .0870607{col 51}{space 1}   -4.13{col 60}{space 3}0.000{col 68}{space 4} .1618651{col 81}{space 3} .5230375
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .9425171{col 40}{space 2} .0852772{col 51}{space 1}   -0.65{col 60}{space 3}0.513{col 68}{space 4} .7893582{col 81}{space 3} 1.125393
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .5184054{col 40}{space 2} .1709007{col 51}{space 1}   -1.99{col 60}{space 3}0.046{col 68}{space 4} .2716797{col 81}{space 3} .9891947
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.160041{col 40}{space 2} .2861413{col 51}{space 1}    0.60{col 60}{space 3}0.547{col 68}{space 4} .7153389{col 81}{space 3} 1.881199
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .2369469{col 40}{space 2} .0873265{col 51}{space 1}   -3.91{col 60}{space 3}0.000{col 68}{space 4} .1150646{col 81}{space 3} .4879332
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.706087{col 40}{space 2} .2527316{col 51}{space 1}    3.61{col 60}{space 3}0.000{col 68}{space 4} 1.276169{col 81}{space 3} 2.280836
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .7465826{col 40}{space 2} .1255913{col 51}{space 1}   -1.74{col 60}{space 3}0.082{col 68}{space 4} .5368925{col 81}{space 3}  1.03817
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.488302{col 40}{space 2} .1468903{col 51}{space 1}    4.03{col 60}{space 3}0.000{col 68}{space 4} 1.226536{col 81}{space 3} 1.805933
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 3.436257{col 40}{space 2} 1.078795{col 51}{space 1}    3.93{col 60}{space 3}0.000{col 68}{space 4} 1.857186{col 81}{space 3} 6.357933
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.367134{col 40}{space 2} .3912907{col 51}{space 1}    1.09{col 60}{space 3}0.275{col 68}{space 4} .7801651{col 81}{space 3} 2.395717
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 1.984802{col 40}{space 2} .4218842{col 51}{space 1}    3.23{col 60}{space 3}0.001{col 68}{space 4} 1.308543{col 81}{space 3} 3.010553
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 3.776343{col 40}{space 2} .9089389{col 51}{space 1}    5.52{col 60}{space 3}0.000{col 68}{space 4} 2.356098{col 81}{space 3} 6.052706
{txt}{space 23}52  {c |}{col 28}{res}{space 2} 2.078133{col 40}{space 2} .7636265{col 51}{space 1}    1.99{col 60}{space 3}0.047{col 68}{space 4} 1.011329{col 81}{space 3} 4.270258
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.512308{col 40}{space 2} .1663887{col 51}{space 1}    3.76{col 60}{space 3}0.000{col 68}{space 4} 1.218957{col 81}{space 3} 1.876255
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.737185{col 40}{space 2}  .351844{col 51}{space 1}    2.73{col 60}{space 3}0.006{col 68}{space 4}  1.16801{col 81}{space 3} 2.583722
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.712431{col 40}{space 2} .5844244{col 51}{space 1}    1.58{col 60}{space 3}0.115{col 68}{space 4}  .877227{col 81}{space 3} 3.342829
{txt}{space 23}56  {c |}{col 28}{res}{space 2}  1.45735{col 40}{space 2} .4884353{col 51}{space 1}    1.12{col 60}{space 3}0.261{col 68}{space 4} .7555809{col 81}{space 3} 2.810908
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} .9529134{col 40}{space 2}  .382963{col 51}{space 1}   -0.12{col 60}{space 3}0.904{col 68}{space 4}  .433478{col 81}{space 3} 2.094787
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3926094{col 40}{space 2} .1012673{col 51}{space 1}   -3.62{col 60}{space 3}0.000{col 68}{space 4} .2368137{col 81}{space 3} .6509004
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .8803898{col 40}{space 2} .1157186{col 51}{space 1}   -0.97{col 60}{space 3}0.332{col 68}{space 4} .6804448{col 81}{space 3} 1.139087
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0791498{col 40}{space 2}  .078035{col 51}{space 1}   -2.57{col 60}{space 3}0.010{col 68}{space 4} .0114614{col 81}{space 3} .5465913
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1905178{col 40}{space 2} .1211122{col 51}{space 1}   -2.61{col 60}{space 3}0.009{col 68}{space 4} .0548058{col 81}{space 3} .6622846
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6645376{col 40}{space 2} .3606237{col 51}{space 1}   -0.75{col 60}{space 3}0.451{col 68}{space 4}  .229403{col 81}{space 3} 1.925041
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2755563{col 40}{space 2} .2109404{col 51}{space 1}   -1.68{col 60}{space 3}0.092{col 68}{space 4} .0614624{col 81}{space 3} 1.235411
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .0002835{col 40}{space 2} .0015558{col 51}{space 1}   -1.49{col 60}{space 3}0.137{col 68}{space 4} 6.04e-09{col 81}{space 3} 13.31214
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9775781{col 40}{space 2} .0310865{col 51}{space 1}   31.45{col 60}{space 3}0.000{col 68}{space 4} .9166498{col 81}{space 3} 1.038506
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.658011{col 40}{space 2} .0826282{col 68}{space 4} 2.500898{col 81}{space 3} 2.824995
{txt}                       1/p {c |}{col 28}{res}{space 2} .3762212{col 40}{space 2} .0116954{col 68}{space 4}  .353983{col 81}{space 3} .3998564
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimate store modelb32a
{txt}
{com}. 
. 
. margins, predict(median time) at(zloytopppdiff=(-0.3960373 0.9692858))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1039.356{col 26}{space 2}  36.5722{col 37}{space 1}   28.42{col 46}{space 3}0.000{col 54}{space 4} 967.6758{col 67}{space 3} 1111.036
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 951.8536{col 26}{space 2} 34.86087{col 37}{space 1}   27.30{col 46}{space 3}0.000{col 54}{space 4} 883.5276{col 67}{space 3}  1020.18
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(zloytopppdiff=(-0.3960373 0.9692858))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     1.93{col 38}{space 2}   0.1649
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-87.50239{col 26}{space 2}  63.0073{col 37}{space 5}-210.9944{col 51}{space 3} 35.98964
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix modelB32azloytopppdiff = r(table)
{txt}
{com}. mat list modelB32azloytopppdiff
{res}
{txt}modelB32azloytopppdiff[9,1]
             r2vs1.
               _at
     b {res} -87.502387
{txt}    se {res}  63.007296
{txt}     z {res} -1.3887659
{txt}pvalue {res}  .16490394
{txt}    ll {res} -210.99442
{txt}    ul {res}  35.989645
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. 
. estimates restore modelb32a
{txt}(results {stata estimates replay modelb32a:modelb32a} are active now)

{com}. 
. margins, predict(median time) at(zloytopppdiff=(-0.6451644 1.711348))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1056.169{col 26}{space 2} 48.22589{col 37}{space 1}   21.90{col 46}{space 3}0.000{col 54}{space 4} 961.6483{col 67}{space 3}  1150.69
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 907.4263{col 26}{space 2}  62.6257{col 37}{space 1}   14.49{col 46}{space 3}0.000{col 54}{space 4} 784.6822{col 67}{space 3}  1030.17
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, predict(median time) at(zloytopppdiff=(-0.6451644 1.711348))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloytopppd~f}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     1.99{col 38}{space 2}   0.1587
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-148.7429{col 26}{space 2} 105.5407{col 37}{space 5}-355.5988{col 51}{space 3} 58.11299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix modelB32bzloytopppdiff = r(table)
{txt}
{com}. mat list modelB32bzloytopppdiff
{res}
{txt}modelB32bzloytopppdiff[9,1]
             r2vs1.
               _at
     b {res} -148.74292
{txt}    se {res}  105.54067
{txt}     z {res} -1.4093422
{txt}pvalue {res}  .15873399
{txt}    ll {res} -355.59883
{txt}    ul {res}  58.112985
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
. **** ALTERNATIVE MECHANISM B4: DOES APPOINTEE LOYALTY TRANSLATE INTO LONGER [SHORTER] SERVICE UNDER LOWER [HIGHER] PRESIDENT-CONGRESSIONAL IDEOLOGICAL POLICY CONFLICT? ***
. 
. 
. 
. 
. **** MODEL B4.1: APPOINTEE LOYALTY X OKSTARTFILIPRESDISTANCE -- COX MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. stcox    c.zloyalmedian##c.okstartfilipresdistance  zpecompmedian  zmecompmedian  soubinaryagency2nom toplevel2 presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean    okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur

{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
Iteration 0:   log pseudolikelihood = {res}-4793.4442
{txt}Iteration 1:   log pseudolikelihood = {res}-4508.6229
{txt}Iteration 2:   log pseudolikelihood = {res}-4481.8559
{txt}Iteration 3:   log pseudolikelihood = {res}-4481.4856
{txt}Iteration 4:   log pseudolikelihood = {res}-4481.4852
{txt}Refining estimates:
Iteration 0:   log pseudolikelihood = {res}-4481.4852

{txt}Cox regression -- Breslow method for ties

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
                                                {txt}Wald chi2({res}40{txt})    =  {res}  50073.95
{txt}Log pseudolikelihood =   {res}-4481.4852             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 106:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 41}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 42}{c |}{col 54}    Robust
{col 1}                                      _t{col 42}{c |} Haz. Ratio{col 54}   Std. Err.{col 66}      z{col 74}   P>|z|{col 82}     [95% Con{col 95}f. Interval]
{hline 41}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 28}zloyalmedian {c |}{col 42}{res}{space 2} 1.365602{col 54}{space 2} .2576903{col 65}{space 1}    1.65{col 74}{space 3}0.099{col 82}{space 4} .9434129{col 95}{space 3} 1.976727
{txt}{space 17}okstartfilipresdistance {c |}{col 42}{res}{space 2} 610.9464{col 54}{space 2} 1442.194{col 65}{space 1}    2.72{col 74}{space 3}0.007{col 82}{space 4} 5.979504{col 95}{space 3} 62422.49
{txt}{space 40} {c |}
c.zloyalmedian#c.okstartfilipresdistance {c |}{col 42}{res}{space 2} .6680787{col 54}{space 2} .1868134{col 65}{space 1}   -1.44{col 74}{space 3}0.149{col 82}{space 4} .3861962{col 95}{space 3} 1.155706
{txt}{space 40} {c |}
{space 27}zpecompmedian {c |}{col 42}{res}{space 2} 1.036341{col 54}{space 2} .0827723{col 65}{space 1}    0.45{col 74}{space 3}0.655{col 82}{space 4} .8861712{col 95}{space 3} 1.211959
{txt}{space 27}zmecompmedian {c |}{col 42}{res}{space 2} .9800701{col 54}{space 2} .0667567{col 65}{space 1}   -0.30{col 74}{space 3}0.768{col 82}{space 4} .8575869{col 95}{space 3} 1.120047
{txt}{space 21}soubinaryagency2nom {c |}{col 42}{res}{space 2} 1.052033{col 54}{space 2} .1750458{col 65}{space 1}    0.30{col 74}{space 3}0.760{col 82}{space 4} .7592754{col 95}{space 3}  1.45767
{txt}{space 31}toplevel2 {c |}{col 42}{res}{space 2} .5000782{col 54}{space 2} .0536061{col 65}{space 1}   -6.46{col 74}{space 3}0.000{col 82}{space 4} .4053153{col 95}{space 3} .6169968
{txt}{space 20}presagencyideolalign {c |}{col 42}{res}{space 2} .6292753{col 54}{space 2} .1533484{col 65}{space 1}   -1.90{col 74}{space 3}0.057{col 82}{space 4} .3903112{col 95}{space 3} 1.014543
{txt}{space 18}presagencyideolopposed {c |}{col 42}{res}{space 2} .6131113{col 54}{space 2} .1582104{col 65}{space 1}   -1.90{col 74}{space 3}0.058{col 82}{space 4} .3697353{col 95}{space 3} 1.016688
{txt}{space 25}subagencydesign {c |}{col 42}{res}{space 2} 1.546114{col 54}{space 2} .2522532{col 65}{space 1}    2.67{col 74}{space 3}0.008{col 82}{space 4} 1.122963{col 95}{space 3} 2.128716
{txt}{space 18}standaloneagencydesign {c |}{col 42}{res}{space 2} 2.014435{col 54}{space 2} .5139693{col 65}{space 1}    2.74{col 74}{space 3}0.006{col 82}{space 4} 1.221729{col 95}{space 3} 3.321479
{txt}{space 14}okstartsenpolarizationmean {c |}{col 42}{res}{space 2} 3.06e-11{col 54}{space 2} 3.22e-10{col 65}{space 1}   -2.30{col 74}{space 3}0.021{col 82}{space 4} 3.39e-20{col 95}{space 3} .0276661
{txt}{space 29}okcrossover {c |}{col 42}{res}{space 2} .1704454{col 54}{space 2} .0388976{col 65}{space 1}   -7.75{col 74}{space 3}0.000{col 82}{space 4} .1089761{col 95}{space 3} .2665873
{txt}{space 26}okstartpresapp {c |}{col 42}{res}{space 2} .9916227{col 54}{space 2}  .004691{col 65}{space 1}   -1.78{col 74}{space 3}0.075{col 82}{space 4}  .982471{col 95}{space 3}  1.00086
{txt}{space 21}okstartunemployment {c |}{col 42}{res}{space 2} 1.118547{col 54}{space 2} .1065392{col 65}{space 1}    1.18{col 74}{space 3}0.240{col 82}{space 4} .9280667{col 95}{space 3} 1.348123
{txt}{space 40} {c |}
{space 29}okstartadyr {c |}
{space 38}2  {c |}{col 42}{res}{space 2}  1.66953{col 54}{space 2} .3723439{col 65}{space 1}    2.30{col 74}{space 3}0.022{col 82}{space 4} 1.078342{col 95}{space 3}  2.58483
{txt}{space 38}3  {c |}{col 42}{res}{space 2}  3.95009{col 54}{space 2}  .913227{col 65}{space 1}    5.94{col 74}{space 3}0.000{col 82}{space 4} 2.510825{col 95}{space 3} 6.214376
{txt}{space 38}4  {c |}{col 42}{res}{space 2} 3.638628{col 54}{space 2} 1.208689{col 65}{space 1}    3.89{col 74}{space 3}0.000{col 82}{space 4} 1.897506{col 95}{space 3} 6.977375
{txt}{space 38}5  {c |}{col 42}{res}{space 2} 1.655154{col 54}{space 2} .4072771{col 65}{space 1}    2.05{col 74}{space 3}0.041{col 82}{space 4} 1.021849{col 95}{space 3} 2.680959
{txt}{space 38}6  {c |}{col 42}{res}{space 2} 3.751533{col 54}{space 2} .9411349{col 65}{space 1}    5.27{col 74}{space 3}0.000{col 82}{space 4} 2.294408{col 95}{space 3} 6.134045
{txt}{space 38}7  {c |}{col 42}{res}{space 2} 5.701458{col 54}{space 2} 1.760138{col 65}{space 1}    5.64{col 74}{space 3}0.000{col 82}{space 4} 3.113189{col 95}{space 3} 10.44159
{txt}{space 38}8  {c |}{col 42}{res}{space 2}   8.6972{col 54}{space 2} 3.433646{col 65}{space 1}    5.48{col 74}{space 3}0.000{col 82}{space 4} 4.011677{col 95}{space 3} 18.85528
{txt}{space 40} {c |}
{space 32}sbagency {c |}
{space 38}2  {c |}{col 42}{res}{space 2} 3.059769{col 54}{space 2}  .776462{col 65}{space 1}    4.41{col 74}{space 3}0.000{col 82}{space 4} 1.860731{col 95}{space 3} 5.031456
{txt}{space 38}3  {c |}{col 42}{res}{space 2} 2.139439{col 54}{space 2} .4788806{col 65}{space 1}    3.40{col 74}{space 3}0.001{col 82}{space 4} 1.379658{col 95}{space 3} 3.317633
{txt}{space 38}4  {c |}{col 42}{res}{space 2} 1.564966{col 54}{space 2} .3300745{col 65}{space 1}    2.12{col 74}{space 3}0.034{col 82}{space 4}  1.03508{col 95}{space 3} 2.366115
{txt}{space 38}5  {c |}{col 42}{res}{space 2} 1.302369{col 54}{space 2} .3215613{col 65}{space 1}    1.07{col 74}{space 3}0.285{col 82}{space 4} .8027274{col 95}{space 3} 2.113002
{txt}{space 38}6  {c |}{col 42}{res}{space 2} 3.015048{col 54}{space 2} .6647157{col 65}{space 1}    5.01{col 74}{space 3}0.000{col 82}{space 4} 1.957191{col 95}{space 3} 4.644675
{txt}{space 38}7  {c |}{col 42}{res}{space 2} 2.069794{col 54}{space 2} .5482631{col 65}{space 1}    2.75{col 74}{space 3}0.006{col 82}{space 4} 1.231557{col 95}{space 3} 3.478564
{txt}{space 38}8  {c |}{col 42}{res}{space 2} 2.661734{col 54}{space 2} .6441281{col 65}{space 1}    4.05{col 74}{space 3}0.000{col 82}{space 4} 1.656447{col 95}{space 3} 4.277123
{txt}{space 38}9  {c |}{col 42}{res}{space 2} 2.231275{col 54}{space 2} .5204191{col 65}{space 1}    3.44{col 74}{space 3}0.001{col 82}{space 4} 1.412603{col 95}{space 3} 3.524407
{txt}{space 37}11  {c |}{col 42}{res}{space 2}  4.09749{col 54}{space 2} 1.214014{col 65}{space 1}    4.76{col 74}{space 3}0.000{col 82}{space 4} 2.292566{col 95}{space 3} 7.323419
{txt}{space 37}12  {c |}{col 42}{res}{space 2} 2.217086{col 54}{space 2} .4140069{col 65}{space 1}    4.26{col 74}{space 3}0.000{col 82}{space 4} 1.537565{col 95}{space 3} 3.196917
{txt}{space 37}13  {c |}{col 42}{res}{space 2} 1.744427{col 54}{space 2} .3799197{col 65}{space 1}    2.55{col 74}{space 3}0.011{col 82}{space 4} 1.138333{col 95}{space 3} 2.673231
{txt}{space 37}14  {c |}{col 42}{res}{space 2}  2.73695{col 54}{space 2} .6695631{col 65}{space 1}    4.12{col 74}{space 3}0.000{col 82}{space 4} 1.694456{col 95}{space 3} 4.420826
{txt}{space 37}15  {c |}{col 42}{res}{space 2} 1.712103{col 54}{space 2} .4003655{col 65}{space 1}    2.30{col 74}{space 3}0.021{col 82}{space 4} 1.082633{col 95}{space 3} 2.707562
{txt}{space 37}16  {c |}{col 42}{res}{space 2} .8879034{col 54}{space 2} .1355069{col 65}{space 1}   -0.78{col 74}{space 3}0.436{col 82}{space 4} .6583549{col 95}{space 3} 1.197489
{txt}{space 37}17  {c |}{col 42}{res}{space 2} 1.668703{col 54}{space 2} .1401136{col 65}{space 1}    6.10{col 74}{space 3}0.000{col 82}{space 4} 1.415492{col 95}{space 3}  1.96721
{txt}{space 37}18  {c |}{col 42}{res}{space 2} 2.245543{col 54}{space 2} .5695847{col 65}{space 1}    3.19{col 74}{space 3}0.001{col 82}{space 4} 1.365881{col 95}{space 3} 3.691728
{txt}{space 37}19  {c |}{col 42}{res}{space 2}  .750533{col 54}{space 2} .1203564{col 65}{space 1}   -1.79{col 74}{space 3}0.074{col 82}{space 4} .5481129{col 95}{space 3} 1.027708
{txt}{space 37}20  {c |}{col 42}{res}{space 2} .2704909{col 54}{space 2} .0843231{col 65}{space 1}   -4.19{col 74}{space 3}0.000{col 82}{space 4} .1468244{col 95}{space 3} .4983184
{txt}{space 37}21  {c |}{col 42}{res}{space 2} .8862263{col 54}{space 2} .0841577{col 65}{space 1}   -1.27{col 74}{space 3}0.203{col 82}{space 4} .7357206{col 95}{space 3} 1.067521
{txt}{space 37}22  {c |}{col 42}{res}{space 2}  .507555{col 54}{space 2} .1763986{col 65}{space 1}   -1.95{col 74}{space 3}0.051{col 82}{space 4} .2568335{col 95}{space 3} 1.003032
{txt}{space 37}23  {c |}{col 42}{res}{space 2}  1.11465{col 54}{space 2}  .264266{col 65}{space 1}    0.46{col 74}{space 3}0.647{col 82}{space 4} .7003769{col 95}{space 3} 1.773965
{txt}{space 37}24  {c |}{col 42}{res}{space 2} .2299169{col 54}{space 2}  .116769{col 65}{space 1}   -2.89{col 74}{space 3}0.004{col 82}{space 4} .0849703{col 95}{space 3} .6221207
{txt}{space 37}25  {c |}{col 42}{res}{space 2} 1.693095{col 54}{space 2}  .230817{col 65}{space 1}    3.86{col 74}{space 3}0.000{col 82}{space 4} 1.296099{col 95}{space 3}  2.21169
{txt}{space 37}26  {c |}{col 42}{res}{space 2} .7683471{col 54}{space 2} .1152459{col 65}{space 1}   -1.76{col 74}{space 3}0.079{col 82}{space 4} .5726431{col 95}{space 3} 1.030934
{txt}{space 37}27  {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 37}28  {c |}{col 42}{res}{space 2} 1.681979{col 54}{space 2}  .162182{col 65}{space 1}    5.39{col 74}{space 3}0.000{col 82}{space 4} 1.392339{col 95}{space 3} 2.031872
{txt}{space 37}29  {c |}{col 42}{res}{space 2} 3.809116{col 54}{space 2} 1.166062{col 65}{space 1}    4.37{col 74}{space 3}0.000{col 82}{space 4} 2.090503{col 95}{space 3} 6.940606
{txt}{space 37}30  {c |}{col 42}{res}{space 2} 1.484754{col 54}{space 2} .3854993{col 65}{space 1}    1.52{col 74}{space 3}0.128{col 82}{space 4} .8925856{col 95}{space 3} 2.469785
{txt}{space 37}50  {c |}{col 42}{res}{space 2} 1.989041{col 54}{space 2} .3511803{col 65}{space 1}    3.89{col 74}{space 3}0.000{col 82}{space 4} 1.407206{col 95}{space 3} 2.811447
{txt}{space 37}51  {c |}{col 42}{res}{space 2} 3.974182{col 54}{space 2} .9553917{col 65}{space 1}    5.74{col 74}{space 3}0.000{col 82}{space 4} 2.480957{col 95}{space 3} 6.366141
{txt}{space 37}52  {c |}{col 42}{res}{space 2} 1.812108{col 54}{space 2} .5847142{col 65}{space 1}    1.84{col 74}{space 3}0.065{col 82}{space 4} .9627783{col 95}{space 3} 3.410687
{txt}{space 37}53  {c |}{col 42}{res}{space 2} 1.612952{col 54}{space 2} .1783395{col 65}{space 1}    4.32{col 74}{space 3}0.000{col 82}{space 4} 1.298693{col 95}{space 3} 2.003256
{txt}{space 37}54  {c |}{col 42}{res}{space 2} 1.758078{col 54}{space 2} .3118792{col 65}{space 1}    3.18{col 74}{space 3}0.001{col 82}{space 4} 1.241758{col 95}{space 3} 2.489083
{txt}{space 37}55  {c |}{col 42}{res}{space 2} 1.747068{col 54}{space 2} .5678094{col 65}{space 1}    1.72{col 74}{space 3}0.086{col 82}{space 4} .9239813{col 95}{space 3} 3.303363
{txt}{space 37}56  {c |}{col 42}{res}{space 2} 1.336005{col 54}{space 2}  .433376{col 65}{space 1}    0.89{col 74}{space 3}0.372{col 82}{space 4} .7074464{col 95}{space 3} 2.523031
{txt}{space 37}57  {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 37}58  {c |}{col 42}{res}{space 2} .9215101{col 54}{space 2} .2683114{col 65}{space 1}   -0.28{col 74}{space 3}0.779{col 82}{space 4} .5207869{col 95}{space 3} 1.630572
{txt}{space 37}59  {c |}{col 42}{res}{space 2} .3269332{col 54}{space 2} .1086051{col 65}{space 1}   -3.37{col 74}{space 3}0.001{col 82}{space 4} .1704886{col 95}{space 3} .6269355
{txt}{space 37}60  {c |}{col 42}{res}{space 2} 1.052775{col 54}{space 2} .1427804{col 65}{space 1}    0.38{col 74}{space 3}0.705{col 82}{space 4} .8070367{col 95}{space 3}  1.37334
{txt}{space 37}61  {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 40} {c |}
{space 34}reagan {c |}{col 42}{res}{space 2} .0724963{col 54}{space 2} .0721786{col 65}{space 1}   -2.64{col 74}{space 3}0.008{col 82}{space 4} .0103002{col 95}{space 3} .5102556
{txt}{space 34}bush41 {c |}{col 42}{res}{space 2} .1822486{col 54}{space 2} .1162689{col 65}{space 1}   -2.67{col 74}{space 3}0.008{col 82}{space 4} .0521944{col 95}{space 3} .6363621
{txt}{space 33}clinton {c |}{col 42}{res}{space 2} .7019291{col 54}{space 2} .3726071{col 65}{space 1}   -0.67{col 74}{space 3}0.505{col 82}{space 4} .2479976{col 95}{space 3} 1.986731
{txt}{space 34}bush43 {c |}{col 42}{res}{space 2} .2758009{col 54}{space 2} .2138085{col 65}{space 1}   -1.66{col 74}{space 3}0.097{col 82}{space 4}  .060356{col 95}{space 3} 1.260291
{txt}{hline 41}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-4793.444{col 39}-4481.485{col 50}    40{col 58}  9042.97{col 69} 9233.248
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}ZLOYALMEDIAN * OKSTARTFILIPRESDISTANCE{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest c.okstartfilipresdistance#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}c.okstartfilipresdistance#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .5765449{col 26}{space 2} .2201147{col 37}{space 1}   -1.44{col 46}{space 3}0.149{col 54}{space 4} .2728094{col 67}{space 3} 1.218448
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB41zloyal = r(table)
{txt}
{com}. mat list modelB41zloyal
{res}
{txt}modelB41zloyal[9,1]
               (1)
     b {res}  .57654486
{txt}    se {res}  .22011466
{txt}     z {res} -1.4424504
{txt}pvalue {res}  .14917535
{txt}    ll {res}  .27280942
{txt}    ul {res}  1.2184476
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          1
{reset}
{com}. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. 
. 
. **** MODEL B4.2: APPOINTEE LOYALTY X OKSTARTFILIPRESDISTANCE -- WEIBULL MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. streg    c.zloyalmedian##c.okstartfilipresdistance  zpecompmedian  zmecompmedian  soubinaryagency2nom toplevel2 presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean   okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43  i. okstartadyr  i.sbagency reagan bush41 clinton bush43,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
note: reagan omitted because of collinearity
note: bush41 omitted because of collinearity
note: clinton omitted because of collinearity
note: bush43 omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-609.56195}  
Iteration 2:{space 3}log pseudolikelihood = {res:-509.22148}  
Iteration 3:{space 3}log pseudolikelihood = {res:-507.98725}  
Iteration 4:{space 3}log pseudolikelihood = {res:-507.98481}  
Iteration 5:{space 3}log pseudolikelihood = {res:-507.98481}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-507.98481             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 106:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 41}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 42}{c |}{col 54}    Robust
{col 1}                                      _t{col 42}{c |} Haz. Ratio{col 54}   Std. Err.{col 66}      z{col 74}   P>|z|{col 82}     [95% Con{col 95}f. Interval]
{hline 41}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 28}zloyalmedian {c |}{col 42}{res}{space 2} 1.374825{col 54}{space 2} .2559065{col 65}{space 1}    1.71{col 74}{space 3}0.087{col 82}{space 4} .9545684{col 95}{space 3} 1.980104
{txt}{space 17}okstartfilipresdistance {c |}{col 42}{res}{space 2} 465.8213{col 54}{space 2} 1094.956{col 65}{space 1}    2.61{col 74}{space 3}0.009{col 82}{space 4} 4.649338{col 95}{space 3} 46671.04
{txt}{space 40} {c |}
c.zloyalmedian#c.okstartfilipresdistance {c |}{col 42}{res}{space 2} .6654764{col 54}{space 2} .1847387{col 65}{space 1}   -1.47{col 74}{space 3}0.142{col 82}{space 4} .3862211{col 95}{space 3} 1.146646
{txt}{space 40} {c |}
{space 27}zpecompmedian {c |}{col 42}{res}{space 2} 1.046042{col 54}{space 2}  .082542{col 65}{space 1}    0.57{col 74}{space 3}0.568{col 82}{space 4} .8961524{col 95}{space 3} 1.221003
{txt}{space 27}zmecompmedian {c |}{col 42}{res}{space 2} .9835304{col 54}{space 2} .0658558{col 65}{space 1}   -0.25{col 74}{space 3}0.804{col 82}{space 4} .8625664{col 95}{space 3} 1.121458
{txt}{space 21}soubinaryagency2nom {c |}{col 42}{res}{space 2} 1.056815{col 54}{space 2} .1812951{col 65}{space 1}    0.32{col 74}{space 3}0.747{col 82}{space 4} .7550514{col 95}{space 3} 1.479181
{txt}{space 31}toplevel2 {c |}{col 42}{res}{space 2} .5262512{col 54}{space 2}  .055898{col 65}{space 1}   -6.04{col 74}{space 3}0.000{col 82}{space 4} .4273454{col 95}{space 3}  .648048
{txt}{space 20}presagencyideolalign {c |}{col 42}{res}{space 2} .7022248{col 54}{space 2} .1631929{col 65}{space 1}   -1.52{col 74}{space 3}0.128{col 82}{space 4} .4453095{col 95}{space 3} 1.107364
{txt}{space 18}presagencyideolopposed {c |}{col 42}{res}{space 2} .6771996{col 54}{space 2} .1667622{col 65}{space 1}   -1.58{col 74}{space 3}0.113{col 82}{space 4} .4179325{col 95}{space 3} 1.097305
{txt}{space 25}subagencydesign {c |}{col 42}{res}{space 2} 1.499176{col 54}{space 2} .2394825{col 65}{space 1}    2.53{col 74}{space 3}0.011{col 82}{space 4} 1.096173{col 95}{space 3}  2.05034
{txt}{space 18}standaloneagencydesign {c |}{col 42}{res}{space 2} 1.742437{col 54}{space 2}  .423547{col 65}{space 1}    2.28{col 74}{space 3}0.022{col 82}{space 4} 1.082055{col 95}{space 3} 2.805853
{txt}{space 14}okstartsenpolarizationmean {c |}{col 42}{res}{space 2} 1.37e-10{col 54}{space 2} 1.44e-09{col 65}{space 1}   -2.16{col 74}{space 3}0.031{col 82}{space 4} 1.52e-19{col 95}{space 3} .1235269
{txt}{space 29}okcrossover {c |}{col 42}{res}{space 2} .1803006{col 54}{space 2} .0402332{col 65}{space 1}   -7.68{col 74}{space 3}0.000{col 82}{space 4} .1164275{col 95}{space 3}  .279215
{txt}{space 26}okstartpresapp {c |}{col 42}{res}{space 2} .9921896{col 54}{space 2} .0047677{col 65}{space 1}   -1.63{col 74}{space 3}0.103{col 82}{space 4}  .982889{col 95}{space 3} 1.001578
{txt}{space 21}okstartunemployment {c |}{col 42}{res}{space 2} 1.107773{col 54}{space 2} .1066562{col 65}{space 1}    1.06{col 74}{space 3}0.288{col 82}{space 4}   .91727{col 95}{space 3}  1.33784
{txt}{space 40} {c |}
{space 29}okstartadyr {c |}
{space 38}2  {c |}{col 42}{res}{space 2} 1.703528{col 54}{space 2} .3737463{col 65}{space 1}    2.43{col 74}{space 3}0.015{col 82}{space 4} 1.108153{col 95}{space 3}  2.61878
{txt}{space 38}3  {c |}{col 42}{res}{space 2} 4.412044{col 54}{space 2} .9704409{col 65}{space 1}    6.75{col 74}{space 3}0.000{col 82}{space 4} 2.866922{col 95}{space 3} 6.789908
{txt}{space 38}4  {c |}{col 42}{res}{space 2}  4.05139{col 54}{space 2} 1.256791{col 65}{space 1}    4.51{col 74}{space 3}0.000{col 82}{space 4} 2.205723{col 95}{space 3} 7.441443
{txt}{space 38}5  {c |}{col 42}{res}{space 2} 1.550249{col 54}{space 2} .3931827{col 65}{space 1}    1.73{col 74}{space 3}0.084{col 82}{space 4} .9430076{col 95}{space 3}  2.54852
{txt}{space 38}6  {c |}{col 42}{res}{space 2} 3.513373{col 54}{space 2} .8990267{col 65}{space 1}    4.91{col 74}{space 3}0.000{col 82}{space 4} 2.127712{col 95}{space 3} 5.801439
{txt}{space 38}7  {c |}{col 42}{res}{space 2} 6.345553{col 54}{space 2} 1.918104{col 65}{space 1}    6.11{col 74}{space 3}0.000{col 82}{space 4}  3.50891{col 95}{space 3} 11.47537
{txt}{space 38}8  {c |}{col 42}{res}{space 2} 9.686523{col 54}{space 2} 3.795347{col 65}{space 1}    5.80{col 74}{space 3}0.000{col 82}{space 4} 4.494201{col 95}{space 3} 20.87774
{txt}{space 40} {c |}
{space 32}sbagency {c |}
{space 38}2  {c |}{col 42}{res}{space 2} 2.711788{col 54}{space 2} .6477784{col 65}{space 1}    4.18{col 74}{space 3}0.000{col 82}{space 4}  1.69795{col 95}{space 3} 4.330983
{txt}{space 38}3  {c |}{col 42}{res}{space 2} 1.906629{col 54}{space 2}  .417339{col 65}{space 1}    2.95{col 74}{space 3}0.003{col 82}{space 4} 1.241504{col 95}{space 3}  2.92809
{txt}{space 38}4  {c |}{col 42}{res}{space 2} 1.436681{col 54}{space 2} .2754509{col 65}{space 1}    1.89{col 74}{space 3}0.059{col 82}{space 4} .9866473{col 95}{space 3} 2.091987
{txt}{space 38}5  {c |}{col 42}{res}{space 2} 1.189802{col 54}{space 2} .2804095{col 65}{space 1}    0.74{col 74}{space 3}0.461{col 82}{space 4} .7496622{col 95}{space 3} 1.888355
{txt}{space 38}6  {c |}{col 42}{res}{space 2} 2.654017{col 54}{space 2} .5699046{col 65}{space 1}    4.55{col 74}{space 3}0.000{col 82}{space 4} 1.742299{col 95}{space 3} 4.042822
{txt}{space 38}7  {c |}{col 42}{res}{space 2} 1.887388{col 54}{space 2} .4812595{col 65}{space 1}    2.49{col 74}{space 3}0.013{col 82}{space 4} 1.145027{col 95}{space 3} 3.111047
{txt}{space 38}8  {c |}{col 42}{res}{space 2}  2.39704{col 54}{space 2} .5389247{col 65}{space 1}    3.89{col 74}{space 3}0.000{col 82}{space 4} 1.542767{col 95}{space 3} 3.724349
{txt}{space 38}9  {c |}{col 42}{res}{space 2} 2.049994{col 54}{space 2}  .451009{col 65}{space 1}    3.26{col 74}{space 3}0.001{col 82}{space 4} 1.331938{col 95}{space 3} 3.155159
{txt}{space 37}11  {c |}{col 42}{res}{space 2}  3.52705{col 54}{space 2} 1.008161{col 65}{space 1}    4.41{col 74}{space 3}0.000{col 82}{space 4}  2.01422{col 95}{space 3}  6.17613
{txt}{space 37}12  {c |}{col 42}{res}{space 2} 2.059407{col 54}{space 2} .3644489{col 65}{space 1}    4.08{col 74}{space 3}0.000{col 82}{space 4} 1.455817{col 95}{space 3} 2.913248
{txt}{space 37}13  {c |}{col 42}{res}{space 2} 1.559015{col 54}{space 2} .3191507{col 65}{space 1}    2.17{col 74}{space 3}0.030{col 82}{space 4} 1.043754{col 95}{space 3} 2.328639
{txt}{space 37}14  {c |}{col 42}{res}{space 2}  2.35557{col 54}{space 2} .5500661{col 65}{space 1}    3.67{col 74}{space 3}0.000{col 82}{space 4} 1.490479{col 95}{space 3}  3.72277
{txt}{space 37}15  {c |}{col 42}{res}{space 2} 1.589749{col 54}{space 2} .3499434{col 65}{space 1}    2.11{col 74}{space 3}0.035{col 82}{space 4} 1.032661{col 95}{space 3} 2.447368
{txt}{space 37}16  {c |}{col 42}{res}{space 2} .8749266{col 54}{space 2} .1420468{col 65}{space 1}   -0.82{col 74}{space 3}0.411{col 82}{space 4} .6364681{col 95}{space 3} 1.202726
{txt}{space 37}17  {c |}{col 42}{res}{space 2} 1.668215{col 54}{space 2} .1452347{col 65}{space 1}    5.88{col 74}{space 3}0.000{col 82}{space 4} 1.406522{col 95}{space 3} 1.978598
{txt}{space 37}18  {c |}{col 42}{res}{space 2} 2.011371{col 54}{space 2} .4792846{col 65}{space 1}    2.93{col 74}{space 3}0.003{col 82}{space 4} 1.260845{col 95}{space 3} 3.208654
{txt}{space 37}19  {c |}{col 42}{res}{space 2} .7513078{col 54}{space 2} .1174389{col 65}{space 1}   -1.83{col 74}{space 3}0.067{col 82}{space 4}   .55305{col 95}{space 3} 1.020637
{txt}{space 37}20  {c |}{col 42}{res}{space 2}   .31784{col 54}{space 2} .0910411{col 65}{space 1}   -4.00{col 74}{space 3}0.000{col 82}{space 4}  .181298{col 95}{space 3} .5572166
{txt}{space 37}21  {c |}{col 42}{res}{space 2} .9211479{col 54}{space 2} .0940922{col 65}{space 1}   -0.80{col 74}{space 3}0.421{col 82}{space 4} .7540185{col 95}{space 3} 1.125322
{txt}{space 37}22  {c |}{col 42}{res}{space 2} .5512706{col 54}{space 2} .1792852{col 65}{space 1}   -1.83{col 74}{space 3}0.067{col 82}{space 4} .2914308{col 95}{space 3} 1.042783
{txt}{space 37}23  {c |}{col 42}{res}{space 2} 1.264635{col 54}{space 2} .2998793{col 65}{space 1}    0.99{col 74}{space 3}0.322{col 82}{space 4}  .794552{col 95}{space 3} 2.012835
{txt}{space 37}24  {c |}{col 42}{res}{space 2} .2529213{col 54}{space 2} .1028505{col 65}{space 1}   -3.38{col 74}{space 3}0.001{col 82}{space 4}  .113984{col 95}{space 3} .5612118
{txt}{space 37}25  {c |}{col 42}{res}{space 2} 1.773389{col 54}{space 2} .2633635{col 65}{space 1}    3.86{col 74}{space 3}0.000{col 82}{space 4} 1.325541{col 95}{space 3} 2.372546
{txt}{space 37}26  {c |}{col 42}{res}{space 2} .7763729{col 54}{space 2}  .128772{col 65}{space 1}   -1.53{col 74}{space 3}0.127{col 82}{space 4}  .560902{col 95}{space 3} 1.074617
{txt}{space 37}27  {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 37}28  {c |}{col 42}{res}{space 2} 1.514238{col 54}{space 2} .1491012{col 65}{space 1}    4.21{col 74}{space 3}0.000{col 82}{space 4} 1.248475{col 95}{space 3} 1.836576
{txt}{space 37}29  {c |}{col 42}{res}{space 2} 3.286115{col 54}{space 2} .9298012{col 65}{space 1}    4.20{col 74}{space 3}0.000{col 82}{space 4} 1.887281{col 95}{space 3} 5.721751
{txt}{space 37}30  {c |}{col 42}{res}{space 2} 1.329831{col 54}{space 2} .3414157{col 65}{space 1}    1.11{col 74}{space 3}0.267{col 82}{space 4} .8040115{col 95}{space 3} 2.199534
{txt}{space 37}50  {c |}{col 42}{res}{space 2}  1.81592{col 54}{space 2} .3117756{col 65}{space 1}    3.47{col 74}{space 3}0.001{col 82}{space 4} 1.297042{col 95}{space 3} 2.542376
{txt}{space 37}51  {c |}{col 42}{res}{space 2} 3.490826{col 54}{space 2} .7870976{col 65}{space 1}    5.54{col 74}{space 3}0.000{col 82}{space 4} 2.243896{col 95}{space 3} 5.430675
{txt}{space 37}52  {c |}{col 42}{res}{space 2} 1.823109{col 54}{space 2} .5739119{col 65}{space 1}    1.91{col 74}{space 3}0.056{col 82}{space 4} .9836841{col 95}{space 3} 3.378855
{txt}{space 37}53  {c |}{col 42}{res}{space 2} 1.574637{col 54}{space 2} .1861772{col 65}{space 1}    3.84{col 74}{space 3}0.000{col 82}{space 4} 1.248931{col 95}{space 3} 1.985282
{txt}{space 37}54  {c |}{col 42}{res}{space 2} 1.589481{col 54}{space 2} .2736818{col 65}{space 1}    2.69{col 74}{space 3}0.007{col 82}{space 4} 1.134209{col 95}{space 3} 2.227501
{txt}{space 37}55  {c |}{col 42}{res}{space 2} 1.467774{col 54}{space 2} .4503218{col 65}{space 1}    1.25{col 74}{space 3}0.211{col 82}{space 4} .8044618{col 95}{space 3} 2.678014
{txt}{space 37}56  {c |}{col 42}{res}{space 2} 1.272403{col 54}{space 2} .3986299{col 65}{space 1}    0.77{col 74}{space 3}0.442{col 82}{space 4} .6885775{col 95}{space 3} 2.351239
{txt}{space 37}57  {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 37}58  {c |}{col 42}{res}{space 2} .7592492{col 54}{space 2} .2352223{col 65}{space 1}   -0.89{col 74}{space 3}0.374{col 82}{space 4} .4136894{col 95}{space 3} 1.393459
{txt}{space 37}59  {c |}{col 42}{res}{space 2} .3473814{col 54}{space 2} .0710286{col 65}{space 1}   -5.17{col 74}{space 3}0.000{col 82}{space 4} .2326818{col 95}{space 3} .5186216
{txt}{space 37}60  {c |}{col 42}{res}{space 2}   .89937{col 54}{space 2} .1219368{col 65}{space 1}   -0.78{col 74}{space 3}0.434{col 82}{space 4} .6894969{col 95}{space 3} 1.173126
{txt}{space 37}61  {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 40} {c |}
{space 34}reagan {c |}{col 42}{res}{space 2} .0817967{col 54}{space 2} .0811383{col 65}{space 1}   -2.52{col 74}{space 3}0.012{col 82}{space 4} .0117054{col 95}{space 3} .5715911
{txt}{space 34}bush41 {c |}{col 42}{res}{space 2} .1877698{col 54}{space 2} .1191955{col 65}{space 1}   -2.63{col 74}{space 3}0.008{col 82}{space 4} .0541111{col 95}{space 3} .6515756
{txt}{space 33}clinton {c |}{col 42}{res}{space 2} .6786843{col 54}{space 2} .3656698{col 65}{space 1}   -0.72{col 74}{space 3}0.472{col 82}{space 4} .2360734{col 95}{space 3}  1.95114
{txt}{space 34}bush43 {c |}{col 42}{res}{space 2} .2817193{col 54}{space 2} .2178706{col 65}{space 1}   -1.64{col 74}{space 3}0.101{col 82}{space 4} .0618772{col 95}{space 3} 1.282633
{txt}{space 34}reagan {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 34}bush41 {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 33}clinton {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 34}bush43 {c |}{col 42}{res}{space 2}        1{col 54}{txt}  (omitted)
{space 35}_cons {c |}{col 42}{res}{space 2} .0004392{col 54}{space 2}  .002404{col 65}{space 1}   -1.41{col 74}{space 3}0.158{col 82}{space 4} 9.62e-09{col 95}{space 3} 20.05135
{txt}{hline 41}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 35}/ln_p {c |}{col 42}{res}{space 2} .9752517{col 54}{space 2} .0309747{col 65}{space 1}   31.49{col 74}{space 3}0.000{col 82}{space 4} .9145423{col 95}{space 3} 1.035961
{txt}{hline 41}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                                       p {c |}{col 42}{res}{space 2} 2.651834{col 54}{space 2} .0821398{col 82}{space 4} 2.495633{col 95}{space 3} 2.817813
{txt}                                     1/p {c |}{col 42}{res}{space 2} .3770974{col 54}{space 2} .0116805{col 82}{space 4} .3548852{col 95}{space 3}    .4007
{txt}{hline 41}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-830.8551{col 39}-507.9848{col 50}    24{col 58}  1063.97{col 69} 1178.136
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}ZLOYALMEDIAN * OKSTARTFILIPRESDISTANCE{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest c.okstartfilipresdistance#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}c.okstartfilipresdistance#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .5734809{col 26}{space 2}   .21736{col 37}{space 1}   -1.47{col 46}{space 3}0.142{col 54}{space 4} .2728334{col 67}{space 3} 1.205425
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB42zloyal = r(table)
{txt}
{com}. mat list modelB42zloyal
{res}
{txt}modelB42zloyal[9,1]
               (1)
     b {res}  .57348085
{txt}    se {res}     .21736
{txt}     z {res} -1.4670269
{txt}pvalue {res}  .14236873
{txt}    ll {res}  .27283342
{txt}    ul {res}  1.2054252
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          1
{reset}
{com}. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. ** Generate 'manual' interaction variable ** 
. generate zloyokppdiff = zloyalmedian*okstartfilipresdistance
{txt}
{com}. 
. ** Re-Estimate Model 3  with 'manual' interaction variable **
. streg    zloyalmedian okstartfilipresdistance zloyokppdiff  zpecompmedian  zmecompmedian  soubinaryagency2nom toplevel2 presagencyideolalign  presagencyideolopposed subagencydesign standaloneagencydesign  okstartsenpolarizationmean   okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43  i. okstartadyr  i.sbagency reagan bush41 clinton bush43,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
note: reagan omitted because of collinearity
note: bush41 omitted because of collinearity
note: clinton omitted because of collinearity
note: bush43 omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-609.56195}  
Iteration 2:{space 3}log pseudolikelihood = {res:-509.22148}  
Iteration 3:{space 3}log pseudolikelihood = {res:-507.98725}  
Iteration 4:{space 3}log pseudolikelihood = {res:-507.98481}  
Iteration 5:{space 3}log pseudolikelihood = {res:-507.98481}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-507.98481             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} 1.374825{col 40}{space 2} .2559065{col 51}{space 1}    1.71{col 60}{space 3}0.087{col 68}{space 4} .9545684{col 81}{space 3} 1.980104
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 465.8213{col 40}{space 2} 1094.956{col 51}{space 1}    2.61{col 60}{space 3}0.009{col 68}{space 4} 4.649338{col 81}{space 3} 46671.04
{txt}{space 14}zloyokppdiff {c |}{col 28}{res}{space 2} .6654764{col 40}{space 2} .1847387{col 51}{space 1}   -1.47{col 60}{space 3}0.142{col 68}{space 4}  .386221{col 81}{space 3} 1.146646
{txt}{space 13}zpecompmedian {c |}{col 28}{res}{space 2} 1.046042{col 40}{space 2}  .082542{col 51}{space 1}    0.57{col 60}{space 3}0.568{col 68}{space 4} .8961524{col 81}{space 3} 1.221003
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9835304{col 40}{space 2} .0658558{col 51}{space 1}   -0.25{col 60}{space 3}0.804{col 68}{space 4} .8625664{col 81}{space 3} 1.121458
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.056815{col 40}{space 2} .1812951{col 51}{space 1}    0.32{col 60}{space 3}0.747{col 68}{space 4} .7550514{col 81}{space 3} 1.479181
{txt}{space 17}toplevel2 {c |}{col 28}{res}{space 2} .5262512{col 40}{space 2}  .055898{col 51}{space 1}   -6.04{col 60}{space 3}0.000{col 68}{space 4} .4273454{col 81}{space 3}  .648048
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .7022248{col 40}{space 2} .1631929{col 51}{space 1}   -1.52{col 60}{space 3}0.128{col 68}{space 4} .4453095{col 81}{space 3} 1.107364
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2} .6771996{col 40}{space 2} .1667622{col 51}{space 1}   -1.58{col 60}{space 3}0.113{col 68}{space 4} .4179325{col 81}{space 3} 1.097305
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.499176{col 40}{space 2} .2394825{col 51}{space 1}    2.53{col 60}{space 3}0.011{col 68}{space 4} 1.096173{col 81}{space 3}  2.05034
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.742437{col 40}{space 2}  .423547{col 51}{space 1}    2.28{col 60}{space 3}0.022{col 68}{space 4} 1.082055{col 81}{space 3} 2.805853
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 1.37e-10{col 40}{space 2} 1.44e-09{col 51}{space 1}   -2.16{col 60}{space 3}0.031{col 68}{space 4} 1.52e-19{col 81}{space 3} .1235269
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2} .1803006{col 40}{space 2} .0402332{col 51}{space 1}   -7.68{col 60}{space 3}0.000{col 68}{space 4} .1164275{col 81}{space 3}  .279215
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9921896{col 40}{space 2} .0047677{col 51}{space 1}   -1.63{col 60}{space 3}0.103{col 68}{space 4}  .982889{col 81}{space 3} 1.001578
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.107773{col 40}{space 2} .1066562{col 51}{space 1}    1.06{col 60}{space 3}0.288{col 68}{space 4}   .91727{col 81}{space 3}  1.33784
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.703528{col 40}{space 2} .3737463{col 51}{space 1}    2.43{col 60}{space 3}0.015{col 68}{space 4} 1.108153{col 81}{space 3}  2.61878
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.412044{col 40}{space 2} .9704409{col 51}{space 1}    6.75{col 60}{space 3}0.000{col 68}{space 4} 2.866922{col 81}{space 3} 6.789908
{txt}{space 24}4  {c |}{col 28}{res}{space 2}  4.05139{col 40}{space 2} 1.256791{col 51}{space 1}    4.51{col 60}{space 3}0.000{col 68}{space 4} 2.205723{col 81}{space 3} 7.441443
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.550249{col 40}{space 2} .3931827{col 51}{space 1}    1.73{col 60}{space 3}0.084{col 68}{space 4} .9430076{col 81}{space 3}  2.54852
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.513373{col 40}{space 2} .8990267{col 51}{space 1}    4.91{col 60}{space 3}0.000{col 68}{space 4} 2.127712{col 81}{space 3} 5.801439
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.345553{col 40}{space 2} 1.918104{col 51}{space 1}    6.11{col 60}{space 3}0.000{col 68}{space 4}  3.50891{col 81}{space 3} 11.47537
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 9.686523{col 40}{space 2} 3.795347{col 51}{space 1}    5.80{col 60}{space 3}0.000{col 68}{space 4} 4.494201{col 81}{space 3} 20.87774
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 2.711788{col 40}{space 2} .6477784{col 51}{space 1}    4.18{col 60}{space 3}0.000{col 68}{space 4}  1.69795{col 81}{space 3} 4.330983
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.906629{col 40}{space 2}  .417339{col 51}{space 1}    2.95{col 60}{space 3}0.003{col 68}{space 4} 1.241504{col 81}{space 3}  2.92809
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.436681{col 40}{space 2} .2754509{col 51}{space 1}    1.89{col 60}{space 3}0.059{col 68}{space 4} .9866473{col 81}{space 3} 2.091987
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.189802{col 40}{space 2} .2804095{col 51}{space 1}    0.74{col 60}{space 3}0.461{col 68}{space 4} .7496622{col 81}{space 3} 1.888355
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 2.654017{col 40}{space 2} .5699046{col 51}{space 1}    4.55{col 60}{space 3}0.000{col 68}{space 4} 1.742299{col 81}{space 3} 4.042822
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.887388{col 40}{space 2} .4812595{col 51}{space 1}    2.49{col 60}{space 3}0.013{col 68}{space 4} 1.145027{col 81}{space 3} 3.111047
{txt}{space 24}8  {c |}{col 28}{res}{space 2}  2.39704{col 40}{space 2} .5389247{col 51}{space 1}    3.89{col 60}{space 3}0.000{col 68}{space 4} 1.542767{col 81}{space 3} 3.724349
{txt}{space 24}9  {c |}{col 28}{res}{space 2} 2.049994{col 40}{space 2}  .451009{col 51}{space 1}    3.26{col 60}{space 3}0.001{col 68}{space 4} 1.331938{col 81}{space 3} 3.155159
{txt}{space 23}11  {c |}{col 28}{res}{space 2}  3.52705{col 40}{space 2} 1.008161{col 51}{space 1}    4.41{col 60}{space 3}0.000{col 68}{space 4}  2.01422{col 81}{space 3}  6.17613
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 2.059407{col 40}{space 2} .3644489{col 51}{space 1}    4.08{col 60}{space 3}0.000{col 68}{space 4} 1.455817{col 81}{space 3} 2.913248
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.559015{col 40}{space 2} .3191507{col 51}{space 1}    2.17{col 60}{space 3}0.030{col 68}{space 4} 1.043754{col 81}{space 3} 2.328639
{txt}{space 23}14  {c |}{col 28}{res}{space 2}  2.35557{col 40}{space 2} .5500661{col 51}{space 1}    3.67{col 60}{space 3}0.000{col 68}{space 4} 1.490479{col 81}{space 3}  3.72277
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.589749{col 40}{space 2} .3499434{col 51}{space 1}    2.11{col 60}{space 3}0.035{col 68}{space 4} 1.032661{col 81}{space 3} 2.447368
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8749266{col 40}{space 2} .1420468{col 51}{space 1}   -0.82{col 60}{space 3}0.411{col 68}{space 4} .6364681{col 81}{space 3} 1.202726
{txt}{space 23}17  {c |}{col 28}{res}{space 2} 1.668215{col 40}{space 2} .1452347{col 51}{space 1}    5.88{col 60}{space 3}0.000{col 68}{space 4} 1.406522{col 81}{space 3} 1.978598
{txt}{space 23}18  {c |}{col 28}{res}{space 2} 2.011371{col 40}{space 2} .4792846{col 51}{space 1}    2.93{col 60}{space 3}0.003{col 68}{space 4} 1.260845{col 81}{space 3} 3.208654
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .7513078{col 40}{space 2} .1174389{col 51}{space 1}   -1.83{col 60}{space 3}0.067{col 68}{space 4}   .55305{col 81}{space 3} 1.020637
{txt}{space 23}20  {c |}{col 28}{res}{space 2}   .31784{col 40}{space 2} .0910411{col 51}{space 1}   -4.00{col 60}{space 3}0.000{col 68}{space 4}  .181298{col 81}{space 3} .5572166
{txt}{space 23}21  {c |}{col 28}{res}{space 2} .9211479{col 40}{space 2} .0940922{col 51}{space 1}   -0.80{col 60}{space 3}0.421{col 68}{space 4} .7540184{col 81}{space 3} 1.125322
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .5512706{col 40}{space 2} .1792852{col 51}{space 1}   -1.83{col 60}{space 3}0.067{col 68}{space 4} .2914308{col 81}{space 3} 1.042783
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.264635{col 40}{space 2} .2998793{col 51}{space 1}    0.99{col 60}{space 3}0.322{col 68}{space 4}  .794552{col 81}{space 3} 2.012835
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .2529213{col 40}{space 2} .1028505{col 51}{space 1}   -3.38{col 60}{space 3}0.001{col 68}{space 4}  .113984{col 81}{space 3} .5612118
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.773389{col 40}{space 2} .2633635{col 51}{space 1}    3.86{col 60}{space 3}0.000{col 68}{space 4} 1.325541{col 81}{space 3} 2.372546
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .7763729{col 40}{space 2}  .128772{col 51}{space 1}   -1.53{col 60}{space 3}0.127{col 68}{space 4}  .560902{col 81}{space 3} 1.074617
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.514238{col 40}{space 2} .1491012{col 51}{space 1}    4.21{col 60}{space 3}0.000{col 68}{space 4} 1.248475{col 81}{space 3} 1.836576
{txt}{space 23}29  {c |}{col 28}{res}{space 2} 3.286115{col 40}{space 2} .9298012{col 51}{space 1}    4.20{col 60}{space 3}0.000{col 68}{space 4} 1.887281{col 81}{space 3} 5.721751
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.329831{col 40}{space 2} .3414157{col 51}{space 1}    1.11{col 60}{space 3}0.267{col 68}{space 4} .8040115{col 81}{space 3} 2.199534
{txt}{space 23}50  {c |}{col 28}{res}{space 2}  1.81592{col 40}{space 2} .3117756{col 51}{space 1}    3.47{col 60}{space 3}0.001{col 68}{space 4} 1.297042{col 81}{space 3} 2.542376
{txt}{space 23}51  {c |}{col 28}{res}{space 2} 3.490826{col 40}{space 2} .7870976{col 51}{space 1}    5.54{col 60}{space 3}0.000{col 68}{space 4} 2.243896{col 81}{space 3} 5.430675
{txt}{space 23}52  {c |}{col 28}{res}{space 2} 1.823109{col 40}{space 2} .5739119{col 51}{space 1}    1.91{col 60}{space 3}0.056{col 68}{space 4} .9836841{col 81}{space 3} 3.378855
{txt}{space 23}53  {c |}{col 28}{res}{space 2} 1.574637{col 40}{space 2} .1861772{col 51}{space 1}    3.84{col 60}{space 3}0.000{col 68}{space 4} 1.248931{col 81}{space 3} 1.985282
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.589481{col 40}{space 2} .2736818{col 51}{space 1}    2.69{col 60}{space 3}0.007{col 68}{space 4} 1.134209{col 81}{space 3} 2.227501
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.467774{col 40}{space 2} .4503218{col 51}{space 1}    1.25{col 60}{space 3}0.211{col 68}{space 4} .8044618{col 81}{space 3} 2.678014
{txt}{space 23}56  {c |}{col 28}{res}{space 2} 1.272403{col 40}{space 2} .3986299{col 51}{space 1}    0.77{col 60}{space 3}0.442{col 68}{space 4} .6885775{col 81}{space 3} 2.351239
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} .7592492{col 40}{space 2} .2352223{col 51}{space 1}   -0.89{col 60}{space 3}0.374{col 68}{space 4} .4136894{col 81}{space 3} 1.393459
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3473814{col 40}{space 2} .0710286{col 51}{space 1}   -5.17{col 60}{space 3}0.000{col 68}{space 4} .2326818{col 81}{space 3} .5186216
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .8993701{col 40}{space 2} .1219368{col 51}{space 1}   -0.78{col 60}{space 3}0.434{col 68}{space 4} .6894969{col 81}{space 3} 1.173126
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0817967{col 40}{space 2} .0811383{col 51}{space 1}   -2.52{col 60}{space 3}0.012{col 68}{space 4} .0117054{col 81}{space 3}  .571591
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1877698{col 40}{space 2} .1191955{col 51}{space 1}   -2.63{col 60}{space 3}0.008{col 68}{space 4} .0541111{col 81}{space 3} .6515756
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6786843{col 40}{space 2} .3656698{col 51}{space 1}   -0.72{col 60}{space 3}0.472{col 68}{space 4} .2360734{col 81}{space 3}  1.95114
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2817193{col 40}{space 2} .2178706{col 51}{space 1}   -1.64{col 60}{space 3}0.101{col 68}{space 4} .0618772{col 81}{space 3} 1.282633
{txt}{space 20}reagan {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 20}bush41 {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 19}clinton {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 20}bush43 {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 21}_cons {c |}{col 28}{res}{space 2} .0004392{col 40}{space 2}  .002404{col 51}{space 1}   -1.41{col 60}{space 3}0.158{col 68}{space 4} 9.62e-09{col 81}{space 3} 20.05135
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9752517{col 40}{space 2} .0309747{col 51}{space 1}   31.49{col 60}{space 3}0.000{col 68}{space 4} .9145423{col 81}{space 3} 1.035961
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.651834{col 40}{space 2} .0821398{col 68}{space 4} 2.495633{col 81}{space 3} 2.817813
{txt}                       1/p {c |}{col 28}{res}{space 2} .3770974{col 40}{space 2} .0116805{col 68}{space 4} .3548852{col 81}{space 3}    .4007
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimate store modelb42a
{txt}
{com}. 
. 
. margins, predict(median time) at(zloyokppdiff=(-0.3960373 0.9692858))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 929.6221{col 26}{space 2} 49.63494{col 37}{space 1}   18.73{col 46}{space 3}0.000{col 54}{space 4} 832.3395{col 67}{space 3} 1026.905
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 1146.485{col 26}{space 2} 108.6432{col 37}{space 1}   10.55{col 46}{space 3}0.000{col 54}{space 4} 933.5482{col 67}{space 3} 1359.422
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(zloyokppdiff=(-0.3960373 0.9692858))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     1.98{col 38}{space 2}   0.1592
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2} 216.8628{col 26}{space 2} 154.0606{col 37}{space 5}-85.09048{col 51}{space 3} 518.8161
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix modelB42azloyokppdiff = r(table)
{txt}
{com}. mat list modelB42azloyokppdiff
{res}
{txt}modelB42azloyokppdiff[9,1]
             r2vs1.
               _at
     b {res}  216.86283
{txt}    se {res}  154.06064
{txt}     z {res}  1.4076459
{txt}pvalue {res}  .15923596
{txt}    ll {res} -85.090485
{txt}    ul {res}  518.81614
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. 
. estimates restore modelb42a
{txt}(results {stata estimates replay modelb42a:modelb42a} are active now)

{com}. 
. margins, predict(median time) at(zloyokppdiff=(-0.6451644 1.711348))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 894.7272{col 26}{space 2} 70.46035{col 37}{space 1}   12.70{col 46}{space 3}0.000{col 54}{space 4} 756.6274{col 67}{space 3} 1032.827
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 1284.876{col 26}{space 2} 221.3867{col 37}{space 1}    5.80{col 46}{space 3}0.000{col 54}{space 4} 850.9659{col 67}{space 3} 1718.786
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, predict(median time) at(zloyokppdiff=(-0.6451644 1.711348))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloyokppdiff}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     1.82{col 38}{space 2}   0.1774
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2} 390.1486{col 26}{space 2} 289.2331{col 37}{space 5}-176.7378{col 51}{space 3} 957.0349
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix modelB42bzloyokppdiff = r(table)
{txt}
{com}. mat list modelB42bzloyokppdiff
{res}
{txt}modelB42bzloyokppdiff[9,1]
             r2vs1.
               _at
     b {res}  390.14856
{txt}    se {res}  289.23305
{txt}     z {res}  1.3489072
{txt}pvalue {res}  .17736677
{txt}    ll {res} -176.73781
{txt}    ul {res}  957.03492
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. 
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. 
. 
. 
. **** ALTERNATIVE MECHANISM B5: DOES APPOINTEE LOYALTY TRANSLATE INTO SHORTER SERVICE IN INDEPENDENT EXECUTIVE AGENCIES COMPARED TO WITHIN EXECUTIVE DEPARTMENTS? WHY? LESS PRESTIGIOUS POSITIONS FOR OCCUPATIONAL OR PROXIMITY TO THE PRESIDENT INFLUENCE ***
. 
. 
. 
. **** MODEL B5.1:  APPOINTEE LOYALTY X STANDALONE AGENCY DESIGN -- COX MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. stcox   c.zloyalmedian##c.standaloneagencydesign  zpecompmedian  zmecompmedian  soubinaryagency2nom toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur

{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity
Iteration 0:   log pseudolikelihood = {res}-4793.4442
{txt}Iteration 1:   log pseudolikelihood = {res}-4507.4251
{txt}Iteration 2:   log pseudolikelihood = {res}-4481.5011
{txt}Iteration 3:   log pseudolikelihood = {res}-4481.1299
{txt}Iteration 4:   log pseudolikelihood = {res}-4481.1295
{txt}Refining estimates:
Iteration 0:   log pseudolikelihood = {res}-4481.1295

{txt}Cox regression -- Breslow method for ties

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
                                                {txt}Wald chi2({res}40{txt})    =  {res}  47018.08
{txt}Log pseudolikelihood =   {res}-4481.1295             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 105:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 40}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 41}{c |}{col 53}    Robust
{col 1}                                     _t{col 41}{c |} Haz. Ratio{col 53}   Std. Err.{col 65}      z{col 73}   P>|z|{col 81}     [95% Con{col 94}f. Interval]
{hline 40}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}zloyalmedian {c |}{col 41}{res}{space 2} .9706288{col 53}{space 2} .0734457{col 64}{space 1}   -0.39{col 73}{space 3}0.694{col 81}{space 4} .8368437{col 94}{space 3} 1.125802
{txt}{space 17}standaloneagencydesign {c |}{col 41}{res}{space 2} 1.727107{col 53}{space 2} .4624245{col 64}{space 1}    2.04{col 73}{space 3}0.041{col 81}{space 4} 1.021914{col 94}{space 3} 2.918935
{txt}{space 39} {c |}
c.zloyalmedian#c.standaloneagencydesign {c |}{col 41}{res}{space 2} 1.289961{col 53}{space 2} .1918121{col 64}{space 1}    1.71{col 73}{space 3}0.087{col 81}{space 4} .9638427{col 94}{space 3} 1.726421
{txt}{space 39} {c |}
{space 26}zpecompmedian {c |}{col 41}{res}{space 2} 1.038985{col 53}{space 2} .0828566{col 64}{space 1}    0.48{col 73}{space 3}0.632{col 81}{space 4}  .888644{col 94}{space 3}  1.21476
{txt}{space 26}zmecompmedian {c |}{col 41}{res}{space 2} .9732996{col 53}{space 2} .0642952{col 64}{space 1}   -0.41{col 73}{space 3}0.682{col 81}{space 4} .8551001{col 94}{space 3} 1.107838
{txt}{space 20}soubinaryagency2nom {c |}{col 41}{res}{space 2} 1.043536{col 53}{space 2} .1753399{col 64}{space 1}    0.25{col 73}{space 3}0.800{col 81}{space 4} .7507312{col 94}{space 3} 1.450542
{txt}{space 30}toplevel2 {c |}{col 41}{res}{space 2} .5029337{col 53}{space 2}  .053887{col 64}{space 1}   -6.41{col 73}{space 3}0.000{col 81}{space 4} .4076698{col 94}{space 3} .6204587
{txt}{space 19}presagencyideolalign {c |}{col 41}{res}{space 2} .6377294{col 53}{space 2} .1571526{col 64}{space 1}   -1.83{col 73}{space 3}0.068{col 81}{space 4} .3934403{col 94}{space 3} 1.033699
{txt}{space 17}presagencyideolopposed {c |}{col 41}{res}{space 2}  .617816{col 53}{space 2} .1576273{col 64}{space 1}   -1.89{col 73}{space 3}0.059{col 81}{space 4} .3747026{col 94}{space 3} 1.018666
{txt}{space 24}subagencydesign {c |}{col 41}{res}{space 2} 1.441765{col 53}{space 2}  .231745{col 64}{space 1}    2.28{col 73}{space 3}0.023{col 81}{space 4} 1.052144{col 94}{space 3} 1.975669
{txt}{space 13}okstartsenpolarizationmean {c |}{col 41}{res}{space 2} 3.14e-11{col 53}{space 2} 3.28e-10{col 64}{space 1}   -2.31{col 73}{space 3}0.021{col 81}{space 4} 3.96e-20{col 94}{space 3} .0248786
{txt}{space 16}okstartfilipresdistance {c |}{col 41}{res}{space 2} 658.1378{col 53}{space 2} 1548.013{col 64}{space 1}    2.76{col 73}{space 3}0.006{col 81}{space 4} 6.549317{col 94}{space 3} 66135.96
{txt}{space 28}okcrossover {c |}{col 41}{res}{space 2} .1687535{col 53}{space 2} .0377288{col 64}{space 1}   -7.96{col 73}{space 3}0.000{col 81}{space 4} .1088796{col 94}{space 3} .2615525
{txt}{space 25}okstartpresapp {c |}{col 41}{res}{space 2} .9911707{col 53}{space 2} .0045912{col 64}{space 1}   -1.91{col 73}{space 3}0.056{col 81}{space 4} .9822129{col 94}{space 3}  1.00021
{txt}{space 20}okstartunemployment {c |}{col 41}{res}{space 2} 1.127752{col 53}{space 2} .1066997{col 64}{space 1}    1.27{col 73}{space 3}0.204{col 81}{space 4} .9368695{col 94}{space 3} 1.357526
{txt}{space 39} {c |}
{space 28}okstartadyr {c |}
{space 37}2  {c |}{col 41}{res}{space 2} 1.644149{col 53}{space 2} .3701579{col 64}{space 1}    2.21{col 73}{space 3}0.027{col 81}{space 4}  1.05756{col 94}{space 3}   2.5561
{txt}{space 37}3  {c |}{col 41}{res}{space 2} 3.943091{col 53}{space 2} .9110113{col 64}{space 1}    5.94{col 73}{space 3}0.000{col 81}{space 4} 2.507121{col 94}{space 3} 6.201522
{txt}{space 37}4  {c |}{col 41}{res}{space 2} 3.739773{col 53}{space 2} 1.212957{col 64}{space 1}    4.07{col 73}{space 3}0.000{col 81}{space 4} 1.980463{col 94}{space 3} 7.061937
{txt}{space 37}5  {c |}{col 41}{res}{space 2} 1.660062{col 53}{space 2} .4033487{col 64}{space 1}    2.09{col 73}{space 3}0.037{col 81}{space 4} 1.031113{col 94}{space 3} 2.672653
{txt}{space 37}6  {c |}{col 41}{res}{space 2}  3.78762{col 53}{space 2} .9494922{col 64}{space 1}    5.31{col 73}{space 3}0.000{col 81}{space 4} 2.317313{col 94}{space 3} 6.190821
{txt}{space 37}7  {c |}{col 41}{res}{space 2} 5.642143{col 53}{space 2} 1.790602{col 64}{space 1}    5.45{col 73}{space 3}0.000{col 81}{space 4}  3.02904{col 94}{space 3} 10.50953
{txt}{space 37}8  {c |}{col 41}{res}{space 2} 8.929433{col 53}{space 2} 3.540304{col 64}{space 1}    5.52{col 73}{space 3}0.000{col 81}{space 4} 4.105282{col 94}{space 3} 19.42248
{txt}{space 39} {c |}
{space 31}sbagency {c |}
{space 37}2  {c |}{col 41}{res}{space 2} 2.905282{col 53}{space 2} .7509254{col 64}{space 1}    4.13{col 73}{space 3}0.000{col 81}{space 4} 1.750569{col 94}{space 3} 4.821671
{txt}{space 37}3  {c |}{col 41}{res}{space 2} 1.992719{col 53}{space 2} .4515386{col 64}{space 1}    3.04{col 73}{space 3}0.002{col 81}{space 4} 1.278112{col 94}{space 3} 3.106873
{txt}{space 37}4  {c |}{col 41}{res}{space 2} 1.573827{col 53}{space 2} .3440876{col 64}{space 1}    2.07{col 73}{space 3}0.038{col 81}{space 4} 1.025316{col 94}{space 3} 2.415773
{txt}{space 37}5  {c |}{col 41}{res}{space 2} 1.271553{col 53}{space 2} .3241251{col 64}{space 1}    0.94{col 73}{space 3}0.346{col 81}{space 4} .7715409{col 94}{space 3} 2.095607
{txt}{space 37}6  {c |}{col 41}{res}{space 2} 3.045511{col 53}{space 2} .6692152{col 64}{space 1}    5.07{col 73}{space 3}0.000{col 81}{space 4} 1.979788{col 94}{space 3} 4.684914
{txt}{space 37}7  {c |}{col 41}{res}{space 2} 1.956021{col 53}{space 2} .5241178{col 64}{space 1}    2.50{col 73}{space 3}0.012{col 81}{space 4} 1.156893{col 94}{space 3}  3.30715
{txt}{space 37}8  {c |}{col 41}{res}{space 2} 2.511311{col 53}{space 2} .6303959{col 64}{space 1}    3.67{col 73}{space 3}0.000{col 81}{space 4} 1.535429{col 94}{space 3} 4.107441
{txt}{space 37}9  {c |}{col 41}{res}{space 2} 2.166563{col 53}{space 2} .5164521{col 64}{space 1}    3.24{col 73}{space 3}0.001{col 81}{space 4} 1.357898{col 94}{space 3} 3.456811
{txt}{space 36}11  {c |}{col 41}{res}{space 2} 3.857862{col 53}{space 2} 1.169552{col 64}{space 1}    4.45{col 73}{space 3}0.000{col 81}{space 4} 2.129589{col 94}{space 3} 6.988719
{txt}{space 36}12  {c |}{col 41}{res}{space 2} 2.108766{col 53}{space 2} .3992055{col 64}{space 1}    3.94{col 73}{space 3}0.000{col 81}{space 4} 1.455089{col 94}{space 3} 3.056099
{txt}{space 36}13  {c |}{col 41}{res}{space 2} 1.688845{col 53}{space 2} .3750216{col 64}{space 1}    2.36{col 73}{space 3}0.018{col 81}{space 4} 1.092883{col 94}{space 3} 2.609792
{txt}{space 36}14  {c |}{col 41}{res}{space 2} 2.624105{col 53}{space 2} .6588786{col 64}{space 1}    3.84{col 73}{space 3}0.000{col 81}{space 4} 1.604189{col 94}{space 3} 4.292466
{txt}{space 36}15  {c |}{col 41}{res}{space 2} 1.598948{col 53}{space 2} .3913651{col 64}{space 1}    1.92{col 73}{space 3}0.055{col 81}{space 4} .9896711{col 94}{space 3} 2.583319
{txt}{space 36}16  {c |}{col 41}{res}{space 2} .8444267{col 53}{space 2} .1278432{col 64}{space 1}   -1.12{col 73}{space 3}0.264{col 81}{space 4} .6276147{col 94}{space 3} 1.136137
{txt}{space 36}17  {c |}{col 41}{res}{space 2} 1.627222{col 53}{space 2} .1368493{col 64}{space 1}    5.79{col 73}{space 3}0.000{col 81}{space 4} 1.379942{col 94}{space 3} 1.918814
{txt}{space 36}18  {c |}{col 41}{res}{space 2}  2.11452{col 53}{space 2} .5579132{col 64}{space 1}    2.84{col 73}{space 3}0.005{col 81}{space 4} 1.260734{col 94}{space 3} 3.546502
{txt}{space 36}19  {c |}{col 41}{res}{space 2} .7141526{col 53}{space 2} .1068185{col 64}{space 1}   -2.25{col 73}{space 3}0.024{col 81}{space 4} .5326888{col 94}{space 3} .9574332
{txt}{space 36}20  {c |}{col 41}{res}{space 2} .3310687{col 53}{space 2} .1082825{col 64}{space 1}   -3.38{col 73}{space 3}0.001{col 81}{space 4} .1743878{col 94}{space 3} .6285216
{txt}{space 36}21  {c |}{col 41}{res}{space 2} .9925052{col 53}{space 2} .1149397{col 64}{space 1}   -0.06{col 73}{space 3}0.948{col 81}{space 4} .7909647{col 94}{space 3} 1.245399
{txt}{space 36}22  {c |}{col 41}{res}{space 2} .5196348{col 53}{space 2} .1846273{col 64}{space 1}   -1.84{col 73}{space 3}0.065{col 81}{space 4}  .258979{col 94}{space 3} 1.042634
{txt}{space 36}23  {c |}{col 41}{res}{space 2} 1.120646{col 53}{space 2} .2699399{col 64}{space 1}    0.47{col 73}{space 3}0.636{col 81}{space 4} .6989272{col 94}{space 3} 1.796821
{txt}{space 36}24  {c |}{col 41}{res}{space 2} .2996376{col 53}{space 2} .1701804{col 64}{space 1}   -2.12{col 73}{space 3}0.034{col 81}{space 4} .0984358{col 94}{space 3} .9120942
{txt}{space 36}25  {c |}{col 41}{res}{space 2} 1.580395{col 53}{space 2} .2245929{col 64}{space 1}    3.22{col 73}{space 3}0.001{col 81}{space 4} 1.196189{col 94}{space 3} 2.088005
{txt}{space 36}26  {c |}{col 41}{res}{space 2} .7993913{col 53}{space 2} .1271862{col 64}{space 1}   -1.41{col 73}{space 3}0.159{col 81}{space 4} .5852346{col 94}{space 3} 1.091915
{txt}{space 36}27  {c |}{col 41}{res}{space 2}        1{col 53}{txt}  (omitted)
{space 36}28  {c |}{col 41}{res}{space 2} 1.628412{col 53}{space 2} .1481089{col 64}{space 1}    5.36{col 73}{space 3}0.000{col 81}{space 4} 1.362527{col 94}{space 3} 1.946183
{txt}{space 36}29  {c |}{col 41}{res}{space 2} 3.612923{col 53}{space 2}  1.13316{col 64}{space 1}    4.10{col 73}{space 3}0.000{col 81}{space 4} 1.953832{col 94}{space 3} 6.680827
{txt}{space 36}30  {c |}{col 41}{res}{space 2} 1.454747{col 53}{space 2} .3971312{col 64}{space 1}    1.37{col 73}{space 3}0.170{col 81}{space 4} .8519579{col 94}{space 3}  2.48403
{txt}{space 36}50  {c |}{col 41}{res}{space 2} 1.928298{col 53}{space 2} .3392368{col 64}{space 1}    3.73{col 73}{space 3}0.000{col 81}{space 4} 1.365922{col 94}{space 3} 2.722213
{txt}{space 36}51  {c |}{col 41}{res}{space 2} 4.021338{col 53}{space 2} .9698779{col 64}{space 1}    5.77{col 73}{space 3}0.000{col 81}{space 4} 2.506544{col 94}{space 3} 6.451576
{txt}{space 36}52  {c |}{col 41}{res}{space 2}   1.8059{col 53}{space 2} .5715725{col 64}{space 1}    1.87{col 73}{space 3}0.062{col 81}{space 4} .9711492{col 94}{space 3}  3.35816
{txt}{space 36}53  {c |}{col 41}{res}{space 2} 1.586575{col 53}{space 2} .1697922{col 64}{space 1}    4.31{col 73}{space 3}0.000{col 81}{space 4} 1.286372{col 94}{space 3} 1.956836
{txt}{space 36}54  {c |}{col 41}{res}{space 2} 1.734053{col 53}{space 2} .3009438{col 64}{space 1}    3.17{col 73}{space 3}0.002{col 81}{space 4} 1.234062{col 94}{space 3}  2.43662
{txt}{space 36}55  {c |}{col 41}{res}{space 2} 1.786044{col 53}{space 2} .5599218{col 64}{space 1}    1.85{col 73}{space 3}0.064{col 81}{space 4} .9661441{col 94}{space 3} 3.301736
{txt}{space 36}56  {c |}{col 41}{res}{space 2} 1.348157{col 53}{space 2} .4309298{col 64}{space 1}    0.93{col 73}{space 3}0.350{col 81}{space 4} .7205417{col 94}{space 3} 2.522444
{txt}{space 36}57  {c |}{col 41}{res}{space 2}        1{col 53}{txt}  (omitted)
{space 36}58  {c |}{col 41}{res}{space 2} .9379946{col 53}{space 2} .2590379{col 64}{space 1}   -0.23{col 73}{space 3}0.817{col 81}{space 4} .5459229{col 94}{space 3} 1.611645
{txt}{space 36}59  {c |}{col 41}{res}{space 2} .3196371{col 53}{space 2} .1050362{col 64}{space 1}   -3.47{col 73}{space 3}0.001{col 81}{space 4} .1678584{col 94}{space 3} .6086551
{txt}{space 36}60  {c |}{col 41}{res}{space 2} 1.057131{col 53}{space 2} .1427768{col 64}{space 1}    0.41{col 73}{space 3}0.681{col 81}{space 4} .8112692{col 94}{space 3} 1.377503
{txt}{space 36}61  {c |}{col 41}{res}{space 2}        1{col 53}{txt}  (omitted)
{space 39} {c |}
{space 33}reagan {c |}{col 41}{res}{space 2} .0696948{col 53}{space 2} .0688204{col 64}{space 1}   -2.70{col 73}{space 3}0.007{col 81}{space 4} .0100619{col 94}{space 3} .4827506
{txt}{space 33}bush41 {c |}{col 41}{res}{space 2} .1835917{col 53}{space 2} .1167507{col 64}{space 1}   -2.67{col 73}{space 3}0.008{col 81}{space 4} .0527901{col 94}{space 3} .6384897
{txt}{space 32}clinton {c |}{col 41}{res}{space 2} .7073126{col 53}{space 2} .3781913{col 64}{space 1}   -0.65{col 73}{space 3}0.517{col 81}{space 4} .2480187{col 94}{space 3} 2.017151
{txt}{space 33}bush43 {c |}{col 41}{res}{space 2} .2699295{col 53}{space 2} .2086943{col 64}{space 1}   -1.69{col 73}{space 3}0.090{col 81}{space 4} .0593129{col 94}{space 3} 1.228433
{txt}{hline 40}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-4793.444{col 39}-4481.129{col 50}    40{col 58} 9042.259{col 69} 9232.536
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}STANDALONE − NON-STANDALONE Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest c.standaloneagencydesign#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}c.standaloneagencydesign#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.415705{col 26}{space 2} .2874138{col 37}{space 1}    1.71{col 46}{space 3}0.087{col 54}{space 4} .9509622{col 67}{space 3}  2.10757
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB51zloyal = r(table)
{txt}
{com}. mat list modelB51zloyal
{res}
{txt}modelB51zloyal[9,1]
              (1)
     b {res} 1.4157046
{txt}    se {res} .28741381
{txt}     z {res} 1.7122965
{txt}pvalue {res} .08684204
{txt}    ll {res} .95096216
{txt}    ul {res} 2.1075702
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. 
. 
. **** MODEL B5.2: APPOINTEE LOYALTY X STANDALONE AGENCY DESIGN -- WEIBULL MODEL [INCLUSION OF BOTH AGENCY AND PRESIDENTIAL ADMINISTRATION FIXED EFFECTS: CLUSTER-ADJUSTED STANDARD ERRORS BY AGENCY] ****
. 
. streg   c.zloyalmedian##c.standaloneagencydesign  zpecompmedian  zmecompmedian  soubinaryagency2nom toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-610.23647}  
Iteration 2:{space 3}log pseudolikelihood = {res:-508.93612}  
Iteration 3:{space 3}log pseudolikelihood = {res:-507.63691}  
Iteration 4:{space 3}log pseudolikelihood = {res:-507.63418}  
Iteration 5:{space 3}log pseudolikelihood = {res:-507.63418}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-507.63418             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 105:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 40}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 41}{c |}{col 53}    Robust
{col 1}                                     _t{col 41}{c |} Haz. Ratio{col 53}   Std. Err.{col 65}      z{col 73}   P>|z|{col 81}     [95% Con{col 94}f. Interval]
{hline 40}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}zloyalmedian {c |}{col 41}{res}{space 2} .9727377{col 53}{space 2} .0745611{col 64}{space 1}   -0.36{col 73}{space 3}0.718{col 81}{space 4} .8370482{col 94}{space 3} 1.130423
{txt}{space 17}standaloneagencydesign {c |}{col 41}{res}{space 2} 1.488272{col 53}{space 2} .3895616{col 64}{space 1}    1.52{col 73}{space 3}0.129{col 81}{space 4} .8909978{col 94}{space 3} 2.485925
{txt}{space 39} {c |}
c.zloyalmedian#c.standaloneagencydesign {c |}{col 41}{res}{space 2} 1.290212{col 53}{space 2} .1973659{col 64}{space 1}    1.67{col 73}{space 3}0.096{col 81}{space 4} .9559852{col 94}{space 3} 1.741289
{txt}{space 39} {c |}
{space 26}zpecompmedian {c |}{col 41}{res}{space 2} 1.048467{col 53}{space 2} .0821918{col 64}{space 1}    0.60{col 73}{space 3}0.546{col 81}{space 4} .8991393{col 94}{space 3} 1.222595
{txt}{space 26}zmecompmedian {c |}{col 41}{res}{space 2} .9772179{col 53}{space 2} .0629733{col 64}{space 1}   -0.36{col 73}{space 3}0.721{col 81}{space 4} .8612689{col 94}{space 3} 1.108777
{txt}{space 20}soubinaryagency2nom {c |}{col 41}{res}{space 2} 1.047104{col 53}{space 2} .1808113{col 64}{space 1}    0.27{col 73}{space 3}0.790{col 81}{space 4} .7464601{col 94}{space 3} 1.468836
{txt}{space 30}toplevel2 {c |}{col 41}{res}{space 2} .5297211{col 53}{space 2} .0558001{col 64}{space 1}   -6.03{col 73}{space 3}0.000{col 81}{space 4} .4309062{col 94}{space 3}  .651196
{txt}{space 19}presagencyideolalign {c |}{col 41}{res}{space 2} .7128614{col 53}{space 2} .1673311{col 64}{space 1}   -1.44{col 73}{space 3}0.149{col 81}{space 4} .4499884{col 94}{space 3} 1.129299
{txt}{space 17}presagencyideolopposed {c |}{col 41}{res}{space 2}  .682713{col 53}{space 2} .1653879{col 64}{space 1}   -1.58{col 73}{space 3}0.115{col 81}{space 4} .4246525{col 94}{space 3} 1.097596
{txt}{space 24}subagencydesign {c |}{col 41}{res}{space 2} 1.395576{col 53}{space 2} .2164259{col 64}{space 1}    2.15{col 73}{space 3}0.032{col 81}{space 4} 1.029791{col 94}{space 3} 1.891289
{txt}{space 13}okstartsenpolarizationmean {c |}{col 41}{res}{space 2} 1.45e-10{col 53}{space 2} 1.51e-09{col 64}{space 1}   -2.18{col 73}{space 3}0.030{col 81}{space 4} 1.99e-19{col 94}{space 3} .1054836
{txt}{space 16}okstartfilipresdistance {c |}{col 41}{res}{space 2} 505.2427{col 53}{space 2} 1181.867{col 64}{space 1}    2.66{col 73}{space 3}0.008{col 81}{space 4} 5.156596{col 94}{space 3} 49503.62
{txt}{space 28}okcrossover {c |}{col 41}{res}{space 2}  .178247{col 53}{space 2} .0389969{col 64}{space 1}   -7.88{col 73}{space 3}0.000{col 81}{space 4} .1160904{col 94}{space 3} .2736833
{txt}{space 25}okstartpresapp {c |}{col 41}{res}{space 2} .9917475{col 53}{space 2}  .004589{col 64}{space 1}   -1.79{col 73}{space 3}0.073{col 81}{space 4} .9827939{col 94}{space 3} 1.000783
{txt}{space 20}okstartunemployment {c |}{col 41}{res}{space 2} 1.116882{col 53}{space 2} .1066352{col 64}{space 1}    1.16{col 73}{space 3}0.247{col 81}{space 4} .9262715{col 94}{space 3} 1.346718
{txt}{space 39} {c |}
{space 28}okstartadyr {c |}
{space 37}2  {c |}{col 41}{res}{space 2} 1.671699{col 53}{space 2} .3721946{col 64}{space 1}    2.31{col 73}{space 3}0.021{col 81}{space 4} 1.080545{col 94}{space 3} 2.586268
{txt}{space 37}3  {c |}{col 41}{res}{space 2} 4.398568{col 53}{space 2} .9679379{col 64}{space 1}    6.73{col 73}{space 3}0.000{col 81}{space 4} 2.857577{col 94}{space 3}  6.77056
{txt}{space 37}4  {c |}{col 41}{res}{space 2} 4.153871{col 53}{space 2} 1.259444{col 64}{space 1}    4.70{col 73}{space 3}0.000{col 81}{space 4} 2.292823{col 94}{space 3}   7.5255
{txt}{space 37}5  {c |}{col 41}{res}{space 2} 1.552477{col 53}{space 2} .3868902{col 64}{space 1}    1.76{col 73}{space 3}0.078{col 81}{space 4} .9525735{col 94}{space 3} 2.530181
{txt}{space 37}6  {c |}{col 41}{res}{space 2} 3.543908{col 53}{space 2} .8995041{col 64}{space 1}    4.98{col 73}{space 3}0.000{col 81}{space 4} 2.154929{col 94}{space 3} 5.828165
{txt}{space 37}7  {c |}{col 41}{res}{space 2} 6.274469{col 53}{space 2} 1.944113{col 64}{space 1}    5.93{col 73}{space 3}0.000{col 81}{space 4} 3.418506{col 94}{space 3} 11.51642
{txt}{space 37}8  {c |}{col 41}{res}{space 2} 9.906058{col 53}{space 2} 3.889284{col 64}{space 1}    5.84{col 73}{space 3}0.000{col 81}{space 4} 4.588861{col 94}{space 3} 21.38439
{txt}{space 39} {c |}
{space 31}sbagency {c |}
{space 37}2  {c |}{col 41}{res}{space 2} 2.574405{col 53}{space 2} .6232028{col 64}{space 1}    3.91{col 73}{space 3}0.000{col 81}{space 4} 1.601847{col 94}{space 3}  4.13745
{txt}{space 37}3  {c |}{col 41}{res}{space 2} 1.770451{col 53}{space 2} .3882196{col 64}{space 1}    2.61{col 73}{space 3}0.009{col 81}{space 4} 1.151953{col 94}{space 3} 2.721028
{txt}{space 37}4  {c |}{col 41}{res}{space 2} 1.450407{col 53}{space 2} .2848422{col 64}{space 1}    1.89{col 73}{space 3}0.058{col 81}{space 4} .9870159{col 94}{space 3} 2.131353
{txt}{space 37}5  {c |}{col 41}{res}{space 2} 1.162849{col 53}{space 2} .2818932{col 64}{space 1}    0.62{col 73}{space 3}0.534{col 81}{space 4} .7230669{col 94}{space 3} 1.870115
{txt}{space 37}6  {c |}{col 41}{res}{space 2}  2.67326{col 53}{space 2} .5726969{col 64}{space 1}    4.59{col 73}{space 3}0.000{col 81}{space 4} 1.756656{col 94}{space 3} 4.068136
{txt}{space 37}7  {c |}{col 41}{res}{space 2} 1.782615{col 53}{space 2} .4577184{col 64}{space 1}    2.25{col 73}{space 3}0.024{col 81}{space 4} 1.077696{col 94}{space 3}  2.94862
{txt}{space 37}8  {c |}{col 41}{res}{space 2} 2.261317{col 53}{space 2} .5278218{col 64}{space 1}    3.50{col 73}{space 3}0.000{col 81}{space 4} 1.431131{col 94}{space 3} 3.573085
{txt}{space 37}9  {c |}{col 41}{res}{space 2}  1.99322{col 53}{space 2} .4450735{col 64}{space 1}    3.09{col 73}{space 3}0.002{col 81}{space 4}  1.28673{col 94}{space 3} 3.087616
{txt}{space 36}11  {c |}{col 41}{res}{space 2}  3.31348{col 53}{space 2} .9719897{col 64}{space 1}    4.08{col 73}{space 3}0.000{col 81}{space 4} 1.864616{col 94}{space 3} 5.888156
{txt}{space 36}12  {c |}{col 41}{res}{space 2} 1.961969{col 53}{space 2}   .34854{col 64}{space 1}    3.79{col 73}{space 3}0.000{col 81}{space 4}  1.38509{col 94}{space 3} 2.779115
{txt}{space 36}13  {c |}{col 41}{res}{space 2} 1.504262{col 53}{space 2} .3124853{col 64}{space 1}    1.97{col 73}{space 3}0.049{col 81}{space 4} 1.001154{col 94}{space 3} 2.260198
{txt}{space 36}14  {c |}{col 41}{res}{space 2} 2.257648{col 53}{space 2}  .539449{col 64}{space 1}    3.41{col 73}{space 3}0.001{col 81}{space 4} 1.413408{col 94}{space 3} 3.606158
{txt}{space 36}15  {c |}{col 41}{res}{space 2} 1.483866{col 53}{space 2} .3401313{col 64}{space 1}    1.72{col 73}{space 3}0.085{col 81}{space 4} .9468526{col 94}{space 3} 2.325449
{txt}{space 36}16  {c |}{col 41}{res}{space 2} .8321287{col 53}{space 2} .1341753{col 64}{space 1}   -1.14{col 73}{space 3}0.254{col 81}{space 4} .6066522{col 94}{space 3} 1.141409
{txt}{space 36}17  {c |}{col 41}{res}{space 2} 1.625226{col 53}{space 2} .1403598{col 64}{space 1}    5.62{col 73}{space 3}0.000{col 81}{space 4} 1.372149{col 94}{space 3}  1.92498
{txt}{space 36}18  {c |}{col 41}{res}{space 2} 1.892687{col 53}{space 2} .4677412{col 64}{space 1}    2.58{col 73}{space 3}0.010{col 81}{space 4}  1.16606{col 94}{space 3} 3.072111
{txt}{space 36}19  {c |}{col 41}{res}{space 2} .7151411{col 53}{space 2} .1045178{col 64}{space 1}   -2.29{col 73}{space 3}0.022{col 81}{space 4} .5370178{col 94}{space 3} .9523461
{txt}{space 36}20  {c |}{col 41}{res}{space 2} .3907434{col 53}{space 2} .1223089{col 64}{space 1}   -3.00{col 73}{space 3}0.003{col 81}{space 4} .2115691{col 94}{space 3} .7216576
{txt}{space 36}21  {c |}{col 41}{res}{space 2} 1.034208{col 53}{space 2}  .133029{col 64}{space 1}    0.26{col 73}{space 3}0.794{col 81}{space 4} .8037461{col 94}{space 3} 1.330752
{txt}{space 36}22  {c |}{col 41}{res}{space 2} .5657651{col 53}{space 2} .1883518{col 64}{space 1}   -1.71{col 73}{space 3}0.087{col 81}{space 4} .2946173{col 94}{space 3} 1.086461
{txt}{space 36}23  {c |}{col 41}{res}{space 2} 1.271658{col 53}{space 2} .3096299{col 64}{space 1}    0.99{col 73}{space 3}0.324{col 81}{space 4} .7890694{col 94}{space 3} 2.049393
{txt}{space 36}24  {c |}{col 41}{res}{space 2} .3372709{col 53}{space 2} .1622069{col 64}{space 1}   -2.26{col 73}{space 3}0.024{col 81}{space 4} .1314021{col 94}{space 3} .8656756
{txt}{space 36}25  {c |}{col 41}{res}{space 2} 1.659097{col 53}{space 2}  .255741{col 64}{space 1}    3.28{col 73}{space 3}0.001{col 81}{space 4} 1.226489{col 94}{space 3} 2.244295
{txt}{space 36}26  {c |}{col 41}{res}{space 2} .8079371{col 53}{space 2} .1443573{col 64}{space 1}   -1.19{col 73}{space 3}0.233{col 81}{space 4} .5692329{col 94}{space 3}  1.14674
{txt}{space 36}27  {c |}{col 41}{res}{space 2}        1{col 53}{txt}  (omitted)
{space 36}28  {c |}{col 41}{res}{space 2} 1.462745{col 53}{space 2} .1369244{col 64}{space 1}    4.06{col 73}{space 3}0.000{col 81}{space 4} 1.217557{col 94}{space 3} 1.757307
{txt}{space 36}29  {c |}{col 41}{res}{space 2}  3.11902{col 53}{space 2} .9017611{col 64}{space 1}    3.93{col 73}{space 3}0.000{col 81}{space 4} 1.769789{col 94}{space 3} 5.496862
{txt}{space 36}30  {c |}{col 41}{res}{space 2} 1.301558{col 53}{space 2} .3492852{col 64}{space 1}    0.98{col 73}{space 3}0.326{col 81}{space 4} .7691938{col 94}{space 3} 2.202376
{txt}{space 36}50  {c |}{col 41}{res}{space 2} 1.761312{col 53}{space 2} .2993238{col 64}{space 1}    3.33{col 73}{space 3}0.001{col 81}{space 4} 1.262351{col 94}{space 3} 2.457495
{txt}{space 36}51  {c |}{col 41}{res}{space 2}  3.53935{col 53}{space 2} .7974952{col 64}{space 1}    5.61{col 73}{space 3}0.000{col 81}{space 4} 2.275771{col 94}{space 3} 5.504506
{txt}{space 36}52  {c |}{col 41}{res}{space 2} 1.818336{col 53}{space 2} .5602186{col 64}{space 1}    1.94{col 73}{space 3}0.052{col 81}{space 4} .9940864{col 94}{space 3} 3.326016
{txt}{space 36}53  {c |}{col 41}{res}{space 2}  1.54726{col 53}{space 2} .1753118{col 64}{space 1}    3.85{col 73}{space 3}0.000{col 81}{space 4} 1.239134{col 94}{space 3} 1.932006
{txt}{space 36}54  {c |}{col 41}{res}{space 2} 1.567224{col 53}{space 2}  .262772{col 64}{space 1}    2.68{col 73}{space 3}0.007{col 81}{space 4} 1.128269{col 94}{space 3} 2.176956
{txt}{space 36}55  {c |}{col 41}{res}{space 2} 1.497429{col 53}{space 2} .4429898{col 64}{space 1}    1.36{col 73}{space 3}0.172{col 81}{space 4} .8385567{col 94}{space 3} 2.673993
{txt}{space 36}56  {c |}{col 41}{res}{space 2} 1.281836{col 53}{space 2} .3961429{col 64}{space 1}    0.80{col 73}{space 3}0.422{col 81}{space 4} .6994781{col 94}{space 3} 2.349041
{txt}{space 36}57  {c |}{col 41}{res}{space 2}        1{col 53}{txt}  (omitted)
{space 36}58  {c |}{col 41}{res}{space 2} .7728055{col 53}{space 2}  .226948{col 64}{space 1}   -0.88{col 73}{space 3}0.380{col 81}{space 4} .4346101{col 94}{space 3}  1.37417
{txt}{space 36}59  {c |}{col 41}{res}{space 2} .3399387{col 53}{space 2} .0702606{col 64}{space 1}   -5.22{col 73}{space 3}0.000{col 81}{space 4} .2267091{col 94}{space 3} .5097205
{txt}{space 36}60  {c |}{col 41}{res}{space 2} .9021865{col 53}{space 2} .1197421{col 64}{space 1}   -0.78{col 73}{space 3}0.438{col 81}{space 4} .6955385{col 94}{space 3} 1.170231
{txt}{space 36}61  {c |}{col 41}{res}{space 2}        1{col 53}{txt}  (omitted)
{space 39} {c |}
{space 33}reagan {c |}{col 41}{res}{space 2} .0783257{col 53}{space 2} .0769566{col 64}{space 1}   -2.59{col 73}{space 3}0.010{col 81}{space 4} .0114178{col 94}{space 3} .5373129
{txt}{space 33}bush41 {c |}{col 41}{res}{space 2} .1887142{col 53}{space 2} .1196366{col 64}{space 1}   -2.63{col 73}{space 3}0.009{col 81}{space 4} .0544728{col 94}{space 3} .6537764
{txt}{space 32}clinton {c |}{col 41}{res}{space 2} .6809095{col 53}{space 2} .3699385{col 64}{space 1}   -0.71{col 73}{space 3}0.479{col 81}{space 4} .2347638{col 94}{space 3} 1.974912
{txt}{space 33}bush43 {c |}{col 41}{res}{space 2} .2743378{col 53}{space 2}   .21186{col 64}{space 1}   -1.67{col 73}{space 3}0.094{col 81}{space 4} .0603861{col 94}{space 3} 1.246334
{txt}{space 34}_cons {c |}{col 41}{res}{space 2} .0004193{col 53}{space 2}   .00227{col 64}{space 1}   -1.44{col 73}{space 3}0.151{col 81}{space 4} 1.03e-08{col 94}{space 3} 17.00579
{txt}{hline 40}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 34}/ln_p {c |}{col 41}{res}{space 2} .9748014{col 53}{space 2}  .030799{col 64}{space 1}   31.65{col 73}{space 3}0.000{col 81}{space 4} .9144365{col 94}{space 3} 1.035166
{txt}{hline 40}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                                      p {c |}{col 41}{res}{space 2} 2.650641{col 53}{space 2}  .081637{col 81}{space 4} 2.495369{col 94}{space 3} 2.815574
{txt}                                    1/p {c |}{col 41}{res}{space 2} .3772673{col 53}{space 2} .0116194{col 81}{space 4} .3551673{col 94}{space 3} .4007424
{txt}{hline 40}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}       860{col 28}-830.8551{col 39}-507.6342{col 50}    24{col 58} 1063.268{col 69} 1177.435
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] BIC note}}.{p_end}

{com}. 
. 
. *** COMPUTE Figure B1: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the HAZARD RATIO of APPOINTEE TENURE {c -(}STANDALONE − NON-STANDALONE Difference{c )-} {c -(}{c -(}2 [M2 & M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}{c )-}. ****
. ** NOTE: IQ = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. lincomest c.standaloneagencydesign#c.zloyalmedian*1.3653231, eform(hr)
{txt}Confidence interval for formula:
{res}c.standaloneagencydesign#c.zloyalmedian*1.3653231

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}         hr{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.416081{col 26}{space 2} .2957567{col 37}{space 1}    1.67{col 46}{space 3}0.096{col 54}{space 4} .9403933{col 67}{space 3} 2.132389
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. matrix modelB52zloyal = r(table)
{txt}
{com}. mat list modelB52zloyal
{res}
{txt}modelB52zloyal[9,1]
              (1)
     b {res} 1.4160806
{txt}    se {res} .29575672
{txt}     z {res} 1.6657081
{txt}pvalue {res} .09577157
{txt}    ll {res} .94039332
{txt}    ul {res} 2.1323888
{txt}    df {res}         .
{txt}  crit {res}  1.959964
{txt} eform {res}         1
{reset}
{com}. 
. 
. 
. **** COMPUTE Figure B2: Interquartile Increase Marginal Effect Change of Appointee Loyalty on the MEDIAN NUMBER OF DAYS OF APPOINTEE TENURE {c -(}PP − NPP Difference{c )-} {c -(}{c -(}4 [M1−M4] × 1 Horizontal Point Estimates and 95% CIs{c )-}.
. ** NOTE: IQR = 1.3653231 [0.9692858 - (-0.3960373)]
. 
. ** Generate 'manual' interaction variable ** 
. generate zloystdppdiff = zloyalmedian*standaloneagencydesign
{txt}
{com}. 
. ** Re-Estimate Model 3  with 'manual' interaction variable **
. streg   zloyalmedian standaloneagencydesign zloystdppdiff  zpecompmedian  zmecompmedian  soubinaryagency2nom toplevel2 presagencyideolalign  presagencyideolopposed  subagencydesign  okstartsenpolarizationmean okstartfilipresdistance   okcrossover okstartpresapp okstartunemployment  i. okstartadyr  i.sbagency reagan bush41 clinton bush43 ,  distribution(weibull) hr vce(cluster sbagency)

         {txt}failure _d:  {res}singleadmin_service
   {txt}analysis time _t:  {res}okapptdur
{txt}note: 27.sbagency omitted because of collinearity
note: 57.sbagency omitted because of collinearity
note: 61.sbagency omitted because of collinearity

Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1012.6928
{txt}Iteration 1:   log pseudolikelihood = {res}-835.21164
{txt}Iteration 2:   log pseudolikelihood = {res}-830.85586
{txt}Iteration 3:   log pseudolikelihood = {res}-830.85509
{txt}Iteration 4:   log pseudolikelihood = {res}-830.85509

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-830.85509}  
Iteration 1:{space 3}log pseudolikelihood = {res:-610.23647}  
Iteration 2:{space 3}log pseudolikelihood = {res:-508.93612}  
Iteration 3:{space 3}log pseudolikelihood = {res:-507.63691}  
Iteration 4:{space 3}log pseudolikelihood = {res:-507.63418}  
Iteration 5:{space 3}log pseudolikelihood = {res:-507.63418}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}         860             {txt}Number of obs    =  {res}       860
{txt}No. of failures      = {res}         831
{txt}Time at risk         = {res}      850034
{col 49}{help j_robustsingular##|_new:Wald chi2(22)}{txt}{col 66}=  {res}         .
{txt}Log pseudolikelihood =   {res}-507.63418             {txt}Prob > chi2      =  {res}         .

{txt}{ralign 92:(Std. Err. adjusted for {res:41} clusters in sbagency)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                        _t{col 28}{c |} Haz. Ratio{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}zloyalmedian {c |}{col 28}{res}{space 2} .9727377{col 40}{space 2} .0745611{col 51}{space 1}   -0.36{col 60}{space 3}0.718{col 68}{space 4} .8370482{col 81}{space 3} 1.130423
{txt}{space 4}standaloneagencydesign {c |}{col 28}{res}{space 2} 1.488272{col 40}{space 2} .3895616{col 51}{space 1}    1.52{col 60}{space 3}0.129{col 68}{space 4} .8909978{col 81}{space 3} 2.485925
{txt}{space 13}zloystdppdiff {c |}{col 28}{res}{space 2} 1.290212{col 40}{space 2} .1973659{col 51}{space 1}    1.67{col 60}{space 3}0.096{col 68}{space 4} .9559852{col 81}{space 3} 1.741289
{txt}{space 13}zpecompmedian {c |}{col 28}{res}{space 2} 1.048467{col 40}{space 2} .0821918{col 51}{space 1}    0.60{col 60}{space 3}0.546{col 68}{space 4} .8991393{col 81}{space 3} 1.222595
{txt}{space 13}zmecompmedian {c |}{col 28}{res}{space 2} .9772179{col 40}{space 2} .0629733{col 51}{space 1}   -0.36{col 60}{space 3}0.721{col 68}{space 4} .8612689{col 81}{space 3} 1.108777
{txt}{space 7}soubinaryagency2nom {c |}{col 28}{res}{space 2} 1.047104{col 40}{space 2} .1808113{col 51}{space 1}    0.27{col 60}{space 3}0.790{col 68}{space 4} .7464601{col 81}{space 3} 1.468836
{txt}{space 17}toplevel2 {c |}{col 28}{res}{space 2} .5297211{col 40}{space 2} .0558001{col 51}{space 1}   -6.03{col 60}{space 3}0.000{col 68}{space 4} .4309062{col 81}{space 3}  .651196
{txt}{space 6}presagencyideolalign {c |}{col 28}{res}{space 2} .7128614{col 40}{space 2} .1673311{col 51}{space 1}   -1.44{col 60}{space 3}0.149{col 68}{space 4} .4499884{col 81}{space 3} 1.129299
{txt}{space 4}presagencyideolopposed {c |}{col 28}{res}{space 2}  .682713{col 40}{space 2} .1653879{col 51}{space 1}   -1.58{col 60}{space 3}0.115{col 68}{space 4} .4246525{col 81}{space 3} 1.097596
{txt}{space 11}subagencydesign {c |}{col 28}{res}{space 2} 1.395576{col 40}{space 2} .2164259{col 51}{space 1}    2.15{col 60}{space 3}0.032{col 68}{space 4} 1.029791{col 81}{space 3} 1.891289
{txt}okstartsenpolarizationmean {c |}{col 28}{res}{space 2} 1.45e-10{col 40}{space 2} 1.51e-09{col 51}{space 1}   -2.18{col 60}{space 3}0.030{col 68}{space 4} 1.99e-19{col 81}{space 3} .1054836
{txt}{space 3}okstartfilipresdistance {c |}{col 28}{res}{space 2} 505.2427{col 40}{space 2} 1181.867{col 51}{space 1}    2.66{col 60}{space 3}0.008{col 68}{space 4} 5.156596{col 81}{space 3} 49503.62
{txt}{space 15}okcrossover {c |}{col 28}{res}{space 2}  .178247{col 40}{space 2} .0389969{col 51}{space 1}   -7.88{col 60}{space 3}0.000{col 68}{space 4} .1160904{col 81}{space 3} .2736833
{txt}{space 12}okstartpresapp {c |}{col 28}{res}{space 2} .9917475{col 40}{space 2}  .004589{col 51}{space 1}   -1.79{col 60}{space 3}0.073{col 68}{space 4} .9827939{col 81}{space 3} 1.000783
{txt}{space 7}okstartunemployment {c |}{col 28}{res}{space 2} 1.116882{col 40}{space 2} .1066352{col 51}{space 1}    1.16{col 60}{space 3}0.247{col 68}{space 4} .9262715{col 81}{space 3} 1.346718
{txt}{space 26} {c |}
{space 15}okstartadyr {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 1.671699{col 40}{space 2} .3721946{col 51}{space 1}    2.31{col 60}{space 3}0.021{col 68}{space 4} 1.080545{col 81}{space 3} 2.586268
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 4.398568{col 40}{space 2} .9679379{col 51}{space 1}    6.73{col 60}{space 3}0.000{col 68}{space 4} 2.857577{col 81}{space 3}  6.77056
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 4.153871{col 40}{space 2} 1.259444{col 51}{space 1}    4.70{col 60}{space 3}0.000{col 68}{space 4} 2.292823{col 81}{space 3}   7.5255
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.552477{col 40}{space 2} .3868902{col 51}{space 1}    1.76{col 60}{space 3}0.078{col 68}{space 4} .9525735{col 81}{space 3} 2.530181
{txt}{space 24}6  {c |}{col 28}{res}{space 2} 3.543908{col 40}{space 2} .8995041{col 51}{space 1}    4.98{col 60}{space 3}0.000{col 68}{space 4} 2.154929{col 81}{space 3} 5.828165
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 6.274469{col 40}{space 2} 1.944113{col 51}{space 1}    5.93{col 60}{space 3}0.000{col 68}{space 4} 3.418506{col 81}{space 3} 11.51642
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 9.906058{col 40}{space 2} 3.889284{col 51}{space 1}    5.84{col 60}{space 3}0.000{col 68}{space 4} 4.588861{col 81}{space 3} 21.38439
{txt}{space 26} {c |}
{space 18}sbagency {c |}
{space 24}2  {c |}{col 28}{res}{space 2} 2.574405{col 40}{space 2} .6232028{col 51}{space 1}    3.91{col 60}{space 3}0.000{col 68}{space 4} 1.601847{col 81}{space 3}  4.13745
{txt}{space 24}3  {c |}{col 28}{res}{space 2} 1.770451{col 40}{space 2} .3882196{col 51}{space 1}    2.61{col 60}{space 3}0.009{col 68}{space 4} 1.151953{col 81}{space 3} 2.721028
{txt}{space 24}4  {c |}{col 28}{res}{space 2} 1.450407{col 40}{space 2} .2848422{col 51}{space 1}    1.89{col 60}{space 3}0.058{col 68}{space 4} .9870159{col 81}{space 3} 2.131353
{txt}{space 24}5  {c |}{col 28}{res}{space 2} 1.162849{col 40}{space 2} .2818932{col 51}{space 1}    0.62{col 60}{space 3}0.534{col 68}{space 4} .7230669{col 81}{space 3} 1.870115
{txt}{space 24}6  {c |}{col 28}{res}{space 2}  2.67326{col 40}{space 2} .5726969{col 51}{space 1}    4.59{col 60}{space 3}0.000{col 68}{space 4} 1.756656{col 81}{space 3} 4.068136
{txt}{space 24}7  {c |}{col 28}{res}{space 2} 1.782615{col 40}{space 2} .4577184{col 51}{space 1}    2.25{col 60}{space 3}0.024{col 68}{space 4} 1.077696{col 81}{space 3}  2.94862
{txt}{space 24}8  {c |}{col 28}{res}{space 2} 2.261317{col 40}{space 2} .5278218{col 51}{space 1}    3.50{col 60}{space 3}0.000{col 68}{space 4} 1.431131{col 81}{space 3} 3.573085
{txt}{space 24}9  {c |}{col 28}{res}{space 2}  1.99322{col 40}{space 2} .4450735{col 51}{space 1}    3.09{col 60}{space 3}0.002{col 68}{space 4}  1.28673{col 81}{space 3} 3.087616
{txt}{space 23}11  {c |}{col 28}{res}{space 2}  3.31348{col 40}{space 2} .9719897{col 51}{space 1}    4.08{col 60}{space 3}0.000{col 68}{space 4} 1.864616{col 81}{space 3} 5.888156
{txt}{space 23}12  {c |}{col 28}{res}{space 2} 1.961969{col 40}{space 2}   .34854{col 51}{space 1}    3.79{col 60}{space 3}0.000{col 68}{space 4}  1.38509{col 81}{space 3} 2.779115
{txt}{space 23}13  {c |}{col 28}{res}{space 2} 1.504262{col 40}{space 2} .3124853{col 51}{space 1}    1.97{col 60}{space 3}0.049{col 68}{space 4} 1.001154{col 81}{space 3} 2.260198
{txt}{space 23}14  {c |}{col 28}{res}{space 2} 2.257648{col 40}{space 2}  .539449{col 51}{space 1}    3.41{col 60}{space 3}0.001{col 68}{space 4} 1.413408{col 81}{space 3} 3.606158
{txt}{space 23}15  {c |}{col 28}{res}{space 2} 1.483866{col 40}{space 2} .3401313{col 51}{space 1}    1.72{col 60}{space 3}0.085{col 68}{space 4} .9468526{col 81}{space 3} 2.325449
{txt}{space 23}16  {c |}{col 28}{res}{space 2} .8321287{col 40}{space 2} .1341753{col 51}{space 1}   -1.14{col 60}{space 3}0.254{col 68}{space 4} .6066522{col 81}{space 3} 1.141409
{txt}{space 23}17  {c |}{col 28}{res}{space 2} 1.625226{col 40}{space 2} .1403598{col 51}{space 1}    5.62{col 60}{space 3}0.000{col 68}{space 4} 1.372149{col 81}{space 3}  1.92498
{txt}{space 23}18  {c |}{col 28}{res}{space 2} 1.892687{col 40}{space 2} .4677412{col 51}{space 1}    2.58{col 60}{space 3}0.010{col 68}{space 4}  1.16606{col 81}{space 3} 3.072111
{txt}{space 23}19  {c |}{col 28}{res}{space 2} .7151411{col 40}{space 2} .1045178{col 51}{space 1}   -2.29{col 60}{space 3}0.022{col 68}{space 4} .5370178{col 81}{space 3} .9523461
{txt}{space 23}20  {c |}{col 28}{res}{space 2} .3907434{col 40}{space 2} .1223089{col 51}{space 1}   -3.00{col 60}{space 3}0.003{col 68}{space 4} .2115691{col 81}{space 3} .7216576
{txt}{space 23}21  {c |}{col 28}{res}{space 2} 1.034208{col 40}{space 2}  .133029{col 51}{space 1}    0.26{col 60}{space 3}0.794{col 68}{space 4} .8037461{col 81}{space 3} 1.330752
{txt}{space 23}22  {c |}{col 28}{res}{space 2} .5657651{col 40}{space 2} .1883518{col 51}{space 1}   -1.71{col 60}{space 3}0.087{col 68}{space 4} .2946173{col 81}{space 3} 1.086461
{txt}{space 23}23  {c |}{col 28}{res}{space 2} 1.271658{col 40}{space 2} .3096299{col 51}{space 1}    0.99{col 60}{space 3}0.324{col 68}{space 4} .7890694{col 81}{space 3} 2.049393
{txt}{space 23}24  {c |}{col 28}{res}{space 2} .3372709{col 40}{space 2} .1622069{col 51}{space 1}   -2.26{col 60}{space 3}0.024{col 68}{space 4} .1314021{col 81}{space 3} .8656756
{txt}{space 23}25  {c |}{col 28}{res}{space 2} 1.659097{col 40}{space 2}  .255741{col 51}{space 1}    3.28{col 60}{space 3}0.001{col 68}{space 4} 1.226489{col 81}{space 3} 2.244295
{txt}{space 23}26  {c |}{col 28}{res}{space 2} .8079371{col 40}{space 2} .1443573{col 51}{space 1}   -1.19{col 60}{space 3}0.233{col 68}{space 4} .5692329{col 81}{space 3}  1.14674
{txt}{space 23}27  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}28  {c |}{col 28}{res}{space 2} 1.462745{col 40}{space 2} .1369244{col 51}{space 1}    4.06{col 60}{space 3}0.000{col 68}{space 4} 1.217557{col 81}{space 3} 1.757307
{txt}{space 23}29  {c |}{col 28}{res}{space 2}  3.11902{col 40}{space 2} .9017611{col 51}{space 1}    3.93{col 60}{space 3}0.000{col 68}{space 4} 1.769789{col 81}{space 3} 5.496862
{txt}{space 23}30  {c |}{col 28}{res}{space 2} 1.301558{col 40}{space 2} .3492852{col 51}{space 1}    0.98{col 60}{space 3}0.326{col 68}{space 4} .7691938{col 81}{space 3} 2.202376
{txt}{space 23}50  {c |}{col 28}{res}{space 2} 1.761312{col 40}{space 2} .2993238{col 51}{space 1}    3.33{col 60}{space 3}0.001{col 68}{space 4} 1.262351{col 81}{space 3} 2.457495
{txt}{space 23}51  {c |}{col 28}{res}{space 2}  3.53935{col 40}{space 2} .7974952{col 51}{space 1}    5.61{col 60}{space 3}0.000{col 68}{space 4} 2.275771{col 81}{space 3} 5.504506
{txt}{space 23}52  {c |}{col 28}{res}{space 2} 1.818336{col 40}{space 2} .5602186{col 51}{space 1}    1.94{col 60}{space 3}0.052{col 68}{space 4} .9940864{col 81}{space 3} 3.326016
{txt}{space 23}53  {c |}{col 28}{res}{space 2}  1.54726{col 40}{space 2} .1753118{col 51}{space 1}    3.85{col 60}{space 3}0.000{col 68}{space 4} 1.239134{col 81}{space 3} 1.932006
{txt}{space 23}54  {c |}{col 28}{res}{space 2} 1.567224{col 40}{space 2}  .262772{col 51}{space 1}    2.68{col 60}{space 3}0.007{col 68}{space 4} 1.128269{col 81}{space 3} 2.176956
{txt}{space 23}55  {c |}{col 28}{res}{space 2} 1.497429{col 40}{space 2} .4429898{col 51}{space 1}    1.36{col 60}{space 3}0.172{col 68}{space 4} .8385567{col 81}{space 3} 2.673993
{txt}{space 23}56  {c |}{col 28}{res}{space 2} 1.281836{col 40}{space 2} .3961429{col 51}{space 1}    0.80{col 60}{space 3}0.422{col 68}{space 4} .6994781{col 81}{space 3} 2.349041
{txt}{space 23}57  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 23}58  {c |}{col 28}{res}{space 2} .7728055{col 40}{space 2}  .226948{col 51}{space 1}   -0.88{col 60}{space 3}0.380{col 68}{space 4} .4346101{col 81}{space 3}  1.37417
{txt}{space 23}59  {c |}{col 28}{res}{space 2} .3399387{col 40}{space 2} .0702606{col 51}{space 1}   -5.22{col 60}{space 3}0.000{col 68}{space 4} .2267091{col 81}{space 3} .5097205
{txt}{space 23}60  {c |}{col 28}{res}{space 2} .9021865{col 40}{space 2} .1197421{col 51}{space 1}   -0.78{col 60}{space 3}0.438{col 68}{space 4} .6955385{col 81}{space 3} 1.170231
{txt}{space 23}61  {c |}{col 28}{res}{space 2}        1{col 40}{txt}  (omitted)
{space 26} {c |}
{space 20}reagan {c |}{col 28}{res}{space 2} .0783257{col 40}{space 2} .0769566{col 51}{space 1}   -2.59{col 60}{space 3}0.010{col 68}{space 4} .0114178{col 81}{space 3} .5373129
{txt}{space 20}bush41 {c |}{col 28}{res}{space 2} .1887142{col 40}{space 2} .1196366{col 51}{space 1}   -2.63{col 60}{space 3}0.009{col 68}{space 4} .0544728{col 81}{space 3} .6537764
{txt}{space 19}clinton {c |}{col 28}{res}{space 2} .6809095{col 40}{space 2} .3699385{col 51}{space 1}   -0.71{col 60}{space 3}0.479{col 68}{space 4} .2347638{col 81}{space 3} 1.974912
{txt}{space 20}bush43 {c |}{col 28}{res}{space 2} .2743378{col 40}{space 2}   .21186{col 51}{space 1}   -1.67{col 60}{space 3}0.094{col 68}{space 4} .0603861{col 81}{space 3} 1.246334
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .0004193{col 40}{space 2}   .00227{col 51}{space 1}   -1.44{col 60}{space 3}0.151{col 68}{space 4} 1.03e-08{col 81}{space 3} 17.00579
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 21}/ln_p {c |}{col 28}{res}{space 2} .9748014{col 40}{space 2}  .030799{col 51}{space 1}   31.65{col 60}{space 3}0.000{col 68}{space 4} .9144365{col 81}{space 3} 1.035166
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                         p {c |}{col 28}{res}{space 2} 2.650641{col 40}{space 2}  .081637{col 68}{space 4} 2.495369{col 81}{space 3} 2.815574
{txt}                       1/p {c |}{col 28}{res}{space 2} .3772673{col 40}{space 2} .0116194{col 68}{space 4} .3551673{col 81}{space 3} .4007424
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimate store modelb52a
{txt}
{com}. 
. 
. margins, predict(median time) at(zloystdppdiff=(-0.3960373 0.9692858))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1039.354{col 26}{space 2} 25.92015{col 37}{space 1}   40.10{col 46}{space 3}0.000{col 54}{space 4} 988.5511{col 67}{space 3} 1090.156
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 911.5129{col 26}{space 2} 57.67823{col 37}{space 1}   15.80{col 46}{space 3}0.000{col 54}{space 4} 798.4656{col 67}{space 3}  1024.56
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. ** Generate Differential Predicted Median Survival Time of Senate Committee Stage of Confirmation Process -- Based on Interquartile Differential [corresponding to Differential Marginal Hazard Ratio Estimates] **
. margins, predict(median time) at(zloystdppdiff=(-0.3960373 0.9692858))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 2}-.3960373}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 3}.9692858}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     2.85{col 38}{space 2}   0.0912
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-127.8408{col 26}{space 2} 75.68301{col 37}{space 5}-276.1768{col 51}{space 3} 20.49518
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. matrix modelB52azloystdppdiff = r(table)
{txt}
{com}. mat list modelB52azloystdppdiff
{res}
{txt}modelB52azloystdppdiff[9,1]
             r2vs1.
               _at
     b {res} -127.84079
{txt}    se {res}  75.683007
{txt}     z {res}  -1.689161
{txt}pvalue {res}  .09118857
{txt}    ll {res} -276.17676
{txt}    ul {res}  20.495181
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. 
. estimates restore modelb52a
{txt}(results {stata estimates replay modelb52a:modelb52a} are active now)

{com}. 
. margins, predict(median time) at(zloystdppdiff=(-0.6451644 1.711348))
{res}
{txt}Predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}_at {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1064.545{col 26}{space 2} 39.78555{col 37}{space 1}   26.76{col 46}{space 3}0.000{col 54}{space 4} 986.5669{col 67}{space 3} 1142.523
{txt}{space 10}2  {c |}{col 14}{res}{space 2} 848.7555{col 26}{space 2}  90.0412{col 37}{space 1}    9.43{col 46}{space 3}0.000{col 54}{space 4}  672.278{col 67}{space 3} 1025.233
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. margins, predict(median time) at(zloystdppdiff=(-0.6451644 1.711348))  contrast(atcontrast(r))
{res}
{txt}Contrasts of predictive margins{col 49}Number of obs{col 67}= {res}       860
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted median _t, predict(median time)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 2}-.6451644}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:zloystdppd~f}{space 4}{txt:=} {space 3}1.711348}{p_end}
{p2colreset}{...}

{res}{col 1}{text}{hline 13}{c TT}{hline 11}{hline 12}{hline 11}
{col 14}{text}{c |}         df{col 26}        chi2{col 38}     P>chi2
{res}{col 1}{text}{hline 13}{c +}{hline 11}{hline 12}{hline 11}
{space 9}_at {res}{col 14}{text}{c |}{result}{space 2}        1{col 26}{space 3}     2.98{col 38}{space 2}   0.0843
{col 1}{text}{hline 13}{c BT}{hline 11}{hline 12}{hline 11}
{res}
{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}   Contrast{col 26}   Std. Err.{col 38}     [95% Con{col 51}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}_at {c |}
{space 3}(2 vs 1)  {c |}{col 14}{res}{space 2}-215.7896{col 26}{space 2} 124.9965{col 37}{space 5}-460.7783{col 51}{space 3} 29.19908
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}
{res}{txt}
{com}. 
. matrix modelB52bzloystdppdiff = r(table)
{txt}
{com}. mat list modelB52bzloystdppdiff
{res}
{txt}modelB52bzloystdppdiff[9,1]
             r2vs1.
               _at
     b {res} -215.78962
{txt}    se {res}  124.99653
{txt}     z {res} -1.7263648
{txt}pvalue {res}   .0842818
{txt}    ll {res} -460.77833
{txt}    ul {res}  29.199085
{txt}    df {res}          .
{txt}  crit {res}   1.959964
{txt} eform {res}          0
{reset}
{com}. 
. 
. ********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. ********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. *Figure B1
. 
. matrix pointmodel = model2zloyal[1,1], model4zloyal[1,1], model2zloyal[7,1], modelB11zmecom[1,1], modelB12zmecom[1,1], modelB21zpecom[1,1], modelB22zpecom[1,1], modelB31zloyal[1,1], modelB32zloyal[1,1], modelB41zloyal[1,1], modelB42zloyal[1,1], modelB51zloyal[1,1], modelB52zloyal[1,1]      
{txt}
{com}. 
. 
. *
. matrix cimodel = (model2zloyal[5,1], model4zloyal[5,1], model2zloyal[7,1], modelB11zmecom[5,1], modelB12zmecom[5,1], modelB21zpecom[5,1], modelB22zpecom[5,1], modelB31zloyal[5,1], modelB32zloyal[5,1], modelB41zloyal[5,1], modelB42zloyal[5,1], modelB51zloyal[5,1], modelB52zloyal[5,1] \ model2zloyal[6,1], model4zloyal[6,1], model2zloyal[7,1], modelB11zmecom[6,1], modelB12zmecom[6,1], modelB21zpecom[6,1], modelB22zpecom[6,1], modelB31zloyal[6,1], modelB32zloyal[6,1], modelB41zloyal[6,1], modelB42zloyal[6,1], modelB51zloyal[6,1], modelB52zloyal[6,1])
{txt}
{com}. 
. 
. 
. coefplot (matrix(pointmodel), ci((cimodel))), grid(none) xline(1, lcolor(red%40) lpattern(dash)) xtitle("Hazard Ratio", size(vsmall) margin(t=2)) ylabel(1 `""Presidential Loyalty x Policy Priority Agencies" "[Model 2]""' 2 `""Presidential Loyalty x Policy Priority Agencies" "[Model 4]""' 3  " " 4 `""Managerial Competence x Policy Priority Agencies" "[Model B1.2]""' 5 `""Managerial Competence x Policy Priority Agencies" "[Model B1.4]""' 6 `""Policy Competence x Policy Priority Agencies" "[Model B2.2]""' 7 `""Policy Competence x Policy Priority Agencies" "[Model B2.4]""' 8 `""Presidential Loyalty x Agency Position Type" "[Model B3.2]""' 9 `""Presidential Loyalty x Agency Position Type" "[Model B3.4]""' 10 `""Presidential Loyalty x  President − Senate Filibuster Distance at Start" "[Model B3.2]""' 11 `""Presidential Loyalty x President − Senate Filibuster Distance at Start" "[Model B3.4]""' 12 `""Presidential Loyalty x Independent Executive Agency" "[Model B4.2]""' 13 `""Presidential Loyalty x Independent Executive Agency" "[Model B4.2]""', labsize(vsmall) noticks) mlabel format(%9.3f) mlabposition(12) mlabsize(vsmall) xlabel(0(1)2, angle(0) labsize(vsmall) format(%9.1f)) msymbol(o) mcolor(black) msize(small) title("FIGURE B1", size(small)) ciopts(lcolor(black)) legend(off) subtitle("Marginal Differential Effect of Alternative Mechanisms Predicting Hazard Ratio of Appointee Tenure", size(vsmall)) xsize(5.5) ysize(3)
{res}{txt}(pointmodel: b missing for some coefficients)
{txt}(pointmodel: CI1 missing for some coefficients)
{res}{txt}
{com}. 
. graph save "Graph" "C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Graphics\FigureB1.gph", replace
{txt}(note: file C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Graphics\FigureB1.gph not found)
{res}{txt}(file C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Graphics\FigureB1.gph saved)

{com}. 
. 
. *************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. *Figure B2
. 
. 
. 
. matrix pointmodel1 = model4azloyal[1,1], model4bzloyal[1,1], model4bzloyal[7,1], modelB12azmecom[1,1], modelB12bzmecom[1,1], modelB22azpecom[1,1], modelB22bzpecom[1,1], modelB32azloytopppdiff[1,1], modelB32bzloytopppdiff[1,1], modelB42azloyokppdiff[1,1], modelB42bzloyokppdiff[1,1], modelB52azloystdppdiff[1,1], modelB52bzloystdppdiff[1,1]
{txt}
{com}. 
. *
. matrix cimodel1 = (model4azloyal[5,1], model4bzloyal[5,1], model4bzloyal[7,1], modelB12azmecom[5,1], modelB12bzmecom[5,1], modelB22azpecom[5,1], modelB22bzpecom[5,1], modelB32azloytopppdiff[5,1], modelB32bzloytopppdiff[5,1], modelB42azloyokppdiff[5,1], modelB42bzloyokppdiff[5,1], modelB52azloystdppdiff[5,1], modelB52bzloystdppdiff[5,1] \ model4azloyal[6,1], model4bzloyal[6,1], model4bzloyal[7,1], modelB12azmecom[6,1], modelB12bzmecom[6,1], modelB22azpecom[6,1], modelB22bzpecom[6,1], modelB32azloytopppdiff[6,1], modelB32bzloytopppdiff[6,1], modelB42azloyokppdiff[6,1], modelB42bzloyokppdiff[6,1], modelB52azloystdppdiff[6,1], modelB52bzloystdppdiff[6,1])
{txt}
{com}. 
. 
. coefplot (matrix(pointmodel1), ci((cimodel1))), grid(none) xline(0, lcolor(red%40) lpattern(dash)) xtitle("Predicted Number of Days", size(vsmall) margin(t=2)) ylabel(1 `""Presidential Loyalty x Policy Priority Agencies" " Interquartile Change [Model 4]""' 2 `""Presidential Loyalty x Policy Priority Agencies" "Interdecile Change [Model 4]""' 3 " " 4 `""Managerial Competence x Policy Priority Agencies" "Interquartile Change [Model B1.2]""' 5 `""Managerial Competence x Policy Priority Agencies" "Interdecile Change [Model B1.4]""' 6 `""Policy Competence x Policy Priority Agencies:" "Interquartile Change [Model B2.2]""' 7 `""Policy Competence x Policy Priority Agencies" "Interdecile Change [Model B2.4]""' 8 `""Presidential Loyalty x Agency Position Type" "Interquartile Change [Model B3.2]""' 9 `""Presidential Loyalty x Agency Position Type" "Interdecile Change [Model B3.4]""' 10 `""Presidential Loyalty x President - Senate Filibuster Distance at Start" "Interquartile Change [Model B3.2]""' 11 `""Presidential Loyalty x President - Senate Filibuster Distance at Start" "Interdecile Change [Model B3.4]""' 12 `""Presidential Loyalty x Independent Executive Agency" "Interquartile Change [Model B4.2]""' 13 `""Presidential Loyalty x Independent Executive Agency" "Interdecile Change [Model B4.4]""', labsize(vsmall) noticks) mlabel format(%9.0f) mlabposition(12) mlabsize(vsmall) xlabel(-500(100)1000, angle(0) labsize(vsmall) format(%9.0f))   msymbol(o) mcolor(black) msize(small) title("FIGURE B2", size(small)) ciopts(lcolor(black)) legend(off) subtitle("Marginal Differential Effect of Alternative Mechanisms Predicting Median Appointee Tenure [Model 4]", size(vsmall)) xsize(5.5) ysize(3)
{res}{txt}(pointmodel1: b missing for some coefficients)
{txt}(pointmodel1: CI1 missing for some coefficients)
{res}{txt}
{com}. 
. graph save "Graph" "C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Graphics\FigureB2.gph", replace
{txt}(note: file C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Graphics\FigureB2.gph not found)
{res}{txt}(file C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Graphics\FigureB2.gph saved)

{com}. 
. *************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\Jason\Dropbox\Jason Byers\Co-Authored Projects\Projects with George Krause\Krause Projects\Confirmation Dynamics Project\Appointee Tenure Project\Jason Byers\March 2023\DART (PRQ)\Output\Hardwiring Committment.APPENDIX B.04-21-2023.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}22 Apr 2023, 09:53:03
{txt}{.-}
{smcl}
{txt}{sf}{ul off}